Prof. Ge Wang Profile

Prof. Ge Wang

Director, Biomedical Imaging Cluster at Rensselaer Polytechnic Institute

SPIE Involvement:

Conference Chair | Editor | Author

Publications (157)

Proceedings Article | 24 October 2024 Presentation + Paper

Impact of network architecture and training strategy for photon counting CT data correction

Bahareh Morovati, Mengzhou Li, Shuo Han, Yongshun Xu, Li Zhou, Ge Wang, Hengyong Yu

Proceedings Volume 13152, 131520D (2024) https://doi.org/10.1117/12.3027262

KEYWORDS: Transformers, Feature extraction, Data corrections, Photon counting, Network architectures, X-ray computed tomography, Sensors, Data modeling, Image segmentation

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Proceedings Article | 24 October 2024 Paper

Compton camera for 3D SPECT imaging

Yuxuan Liang, Mengzhou Li, Shuo Han, Hengyong Yu, Ge Wang

Proceedings Volume 13152, 1315224 (2024) https://doi.org/10.1117/12.3028247

KEYWORDS: Single photon emission computed tomography, Compton scattering, Imaging systems

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Proceedings Article | 23 October 2024 Presentation + Paper

Oxygenation imaging of deep targets at high resolution with an x-ray luminescence micro-CT system

Yibing Zhang, Yile Fang, Vigjna Abbaraju, Jeffrey Anker, Wenxiang Cong, Ge Wang, Changqing Li

Proceedings Volume 13152, 1315218 (2024) https://doi.org/10.1117/12.3027929

KEYWORDS: Oxygen, X-rays, Oxygenation, Sensors, Photons, Image restoration, Imaging systems, X-ray imaging, Image sensors, X-ray computed tomography

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Proceedings Article | 23 October 2024 Paper

A 3D-printed table for hybrid x-ray CT and optical imaging of a live mouse

Wenxuan Xue, Yuxuan Liang, Mengzhou Li, Shan Gao, Xavier Intes, Ge Wang

Proceedings Volume 13152, 131521L (2024) https://doi.org/10.1117/12.3029550

KEYWORDS: Imaging systems, Computed tomography, Optical imaging, Animals

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Proceedings Article | 23 October 2024 Presentation + Paper

Ulrich Bonse’s lasting influence through x-ray interference

Ge Wang

Proceedings Volume 13152, 131521J (2024) https://doi.org/10.1117/12.3028818

KEYWORDS: Artificial intelligence, Data modeling, X-ray imaging, Tomography, Interferometry, X-ray computed tomography, Machine learning

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Proceedings Article | 17 October 2024 Presentation + Paper

Interior photon-counting CT data denoising via multi-agent reinforcement learning

Md Sayed Tanveer, Christopher Wiedeman, Yongyi Shi, Hengyong Yu, Ge Wang

Proceedings Volume 13152, 131520C (2024) https://doi.org/10.1117/12.3029551

KEYWORDS: Denoising, Image restoration, Data modeling, Computed tomography, Reconstruction algorithms

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Proceedings Article | 10 April 2023 Presentation + Paper

Development of fast and three-dimensional focused x-ray luminescence tomography system

Yile Fang, Yibing Zhang, Michael Lun, Jeffrey Anker, Ge Wang, Changqing Li

Proceedings Volume 12468, 124680Z (2023) https://doi.org/10.1117/12.2654091

KEYWORDS: X-rays, Imaging systems, X-ray imaging, Image restoration, Luminescence, Photon counting, Spatial resolution, Calibration, Reconstruction algorithms, 3D image processing

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Proceedings Article | 10 April 2023 Presentation + Paper

Oxygenation imaging in deep tissue with X-ray Luminescence Computed Tomography (XLCT)

Yibing Zhang, Yile Fang, Vigjna Abbaraju, Sriparna Bhattacharya, Jeffrey Anker, Ge Wang, Changqing Li

Proceedings Volume 12468, 124680I (2023) https://doi.org/10.1117/12.2654446

KEYWORDS: Oxygenation, X-rays, Image restoration, X-ray imaging, Tissues, Photons, X-ray technology, X-ray fluorescence spectroscopy, Luminescence, Bone

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Proceedings Article | 7 April 2023 Poster + Paper

Computational method to artificially insert clusters of microcalcifications in digital breast tomosynthesis

Rodrigo Vimieiro, Lucas Borges, Bruno Barufaldi, Andrew D. Maidment, Renato Caron, Silvia M. P. Sabino, Ge Wang, Marcelo A. Vieira

Proceedings Volume 12463, 124632N (2023) https://doi.org/10.1117/12.2653857

KEYWORDS: Digital breast tomosynthesis, Medical imaging, Computer simulations, Modulation transfer functions, Breast cancer, Voxels, Image processing, Cancer detection, Breast

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Proceedings Article | 10 November 2022 Presentation + Paper

Multi-view x-ray dissectography improves nodule detection

Chuang Niu, Giridhar Dasegowda, Pingkun Yan, Mannudeep Kalra, Ge Wang

Proceedings Volume 12242, 1224217 (2022) https://doi.org/10.1117/12.2637782

KEYWORDS: Lung, X-rays, Radiography, X-ray imaging, Sensors, 3D image processing, X-ray computed tomography, Detection and tracking algorithms, 3D modeling, Lung cancer

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Proceedings Article | 10 November 2022 Presentation + Paper

A data generation pipeline for cardiac vessel segmentation and motion artifact grading

Asif Sushmit, Yongshun Xu, Olivia Mariani, Qing Lyu, Ying Li, Ximiao Cao, Christopher Wiedeman, Hongfeng Ma, Jonathan Maltz, Hengyong Yu, Ge Wang

Proceedings Volume 12242, 122421J (2022) https://doi.org/10.1117/12.2642869

KEYWORDS: Data modeling, Computed tomography, Image segmentation, Heart, Image quality, Pathology, Performance modeling, Motion models, Arteries, Scanners

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Proceedings Article | 18 October 2022 Open Access

X-ray dissectography enables stereotography

Chuang Niu, Ge Wang

Proceedings Volume 12304, 123041T (2022) https://doi.org/10.1117/12.2647278

KEYWORDS: X-rays, Radiography, X-ray imaging, 3D acquisition, Lung, Imaging systems, Image segmentation, X-ray computed tomography, 3D image processing, Tomography

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Proceedings Article | 18 October 2022 Open Access

Motion correction via locally linear embedding for helical photon-counting CT

Mengzhou Li, Chiara Lowe, Anthony Butler, Phil Butler, Ge Wang

Proceedings Volume 12304, 123042I (2022) https://doi.org/10.1117/12.2646714

KEYWORDS: Motion estimation, Sensors, X-ray computed tomography, Reconstruction algorithms, Motion measurement, Photodetectors, Image quality, CT reconstruction, Image restoration, Computed tomography

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Proceedings Article | 14 October 2022 Presentation + Paper

Motion correction for robot-based x-ray photon-counting CT at ultrahigh resolution

Mengzhou Li, Jana Bohacova, Josef Uher, Wenxiang Cong, Jay Rubinstein, Ge Wang

Proceedings Volume 12242, 122420Y (2022) https://doi.org/10.1117/12.2635263

KEYWORDS: Sensors, Robotics, X-ray computed tomography, X-rays, Scanners, Calibration, Image resolution, Imaging systems, X-ray sources, Reconstruction algorithms

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Ultrahigh-resolution CT is highly desirable in many clinical applications, such as cochlear implantation and coronary stenosis assessment. Despite the wide accessibility to micro-CT for preclinical research, there are no such micro-CT scanners for clinical use, due to several issues including high radiation dose, patient movement, limited X-ray source power and long image time. To meet the challenge, here we design a robotic-arm-based clinical photon-counting micro-CT system in the interior tomography mode for temporal bone imaging at a 50 µm resolution. We adopt twin collaborative robotic arms. These robotic arms can be operated near humans without danger of injury due to collision. One robot steers the source, the other the detector. The six-axis robot pair defines a volume of interest (VOI) more flexibly than the traditional rotation gantries and C-arm systems. The robotic system allows arbitrary imaging geometry. The required spatial resolution is on the same order of the robot mechanical precision, therefore the geometric errors due to robotic coordination together with patient motion, and system misalignment must be addressed. In this paper, we propose a locally linear embedding-based motion correction method to solve this problem to correct all these geometric errors in an unified framework with a nine-degree-of-freedom model. Different from the conventional motion correction methods that rely on gradient-based parametric optimization, our method utilizes a parametric searching mechanism through iterative reconstruction and without assuming any smoothness of the errors as a function of the view angle. The effectiveness of our method is first demonstrated with numerical simulation and further verified on a set of limited-angle cone-beam scans of a sacrificed mouse using our robotic-arm-based imaging system. Sharper images with clearer anatomical details in the absence of misalignment artifacts are obtained after our data-driven geometric calibration, suggesting a great potential of our method in biomedical and industrial applications.

Proceedings Article | 14 October 2022 Presentation + Paper

Metal pin artifact reduction with masked iterative nano-CT reconstruction

Mengzhou Li, Victoria Cooley, Viktor Nikitin, Stuart Stock, Ge Wang

Proceedings Volume 12242, 122421H (2022) https://doi.org/10.1117/12.2635261

KEYWORDS: Metals, Image segmentation, Teeth, Tomography, Lawrencium, Image quality, X-rays, Synchrotron radiation, Signal attenuation, X-ray microscopy, X-ray computed tomography

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Proceedings Article | 14 October 2022 Presentation + Paper

Self-supervised dual-domain network for low-dose CT denoising

Chuang Niu, Mengzhou Li, Xiaodong Guo, Ge Wang

Proceedings Volume 12242, 122420H (2022) https://doi.org/10.1117/12.2633197

KEYWORDS: Denoising, Image processing, X-ray computed tomography, Reconstruction algorithms, Signal attenuation, Data modeling, Computed tomography, Image quality, Radiation effects, Machine learning

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Proceedings Article | 13 July 2022 Paper

Imposing noise correlation fidelity on digital breast tomosynthesis restoration through deep learning techniques

Rodrigo Vimieiro, Lucas Borges, Ge Wang, Marcelo A. C. Vieira

Proceedings Volume 12286, 122861C (2022) https://doi.org/10.1117/12.2626634

KEYWORDS: Picosecond phenomena, Digital breast tomosynthesis, Image restoration, Breast, Visualization, Breast cancer, Neural networks, Image quality, Denoising, Zoom lenses

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Proceedings Article | 13 July 2022 Paper

Suppressing noise correlation in digital breast tomosynthesis using convolutional neural network and virtual clinical trials

Rodrigo Vimieiro, Lucas Borges, Renato Caron, Bruno Barufaldi, Andrew D. A. Maidment, Ge Wang, Marcelo A. C. Vieira

Proceedings Volume 12286, 122861B (2022) https://doi.org/10.1117/12.2625357

KEYWORDS: Digital breast tomosynthesis, Picosecond phenomena, Image restoration, Quantum electronics, Denoising, Convolutional neural networks, Clinical trials, Sensors, Computer simulations, Breast

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SPIE Journal Paper | 30 June 2022 Open Access

Special Section Guest Editorial: Hard X-Ray Tomography with Micrometer Resolution

Bert Müller, Stuart Stock, Ge Wang, Jovan Brankov

JMI, Vol. 9, Issue 03, 031501, (June 2022) https://doi.org/10.1117/12.10.1117/1.JMI.9.3.031501

KEYWORDS: Tomography, Hard x-rays, X-rays, X-ray imaging, Teeth, Computed tomography, Tumors, Spatial resolution, Reconstruction algorithms, Radiography

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Proceedings Article | 4 April 2022 Poster + Presentation + Paper

Assessment of training strategies for convolutional neural network to restore low-dose digital breast tomosynthesis projections

Rodrigo de Barros Vimieiro, Lucas Rodrigues Borges, Bruno Barufaldi, Andrew Maidment, Ge Wang, Marcelo Andrade da Costa Vieira

Proceedings Volume 12031, 120311V (2022) https://doi.org/10.1117/12.2609945

KEYWORDS: Digital breast tomosynthesis, Breast, Signal to noise ratio, Image restoration, Denoising, Network architectures

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Proceedings Article | 4 April 2022 Poster + Paper

Effects of image denoising on quantitative material decomposition in photon-counting spectral computed tomography

Connor Evans, Mengzhou Li, Chuang Niu, Ge Wang, Ryan Roeder

Proceedings Volume 12031, 120312Y (2022) https://doi.org/10.1117/12.2611828

KEYWORDS: Gadolinium, Image denoising, Calcium, Iodine, Spatial resolution, Tissues, Image quality, Image classification, Spectral computed tomography, X-ray computed tomography, X-ray medical imaging

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Material decomposition algorithms enable discrimination and quantification of multiple contrast agent and tissue compositions in spectral image datasets acquired by photon-counting computed tomography (PCCT). Image denoising has been shown to improve PCCT image reconstruction quality and feature recognition while preserving fine image detail. Reduction of image artifacts and noise could also improve the accuracy of material decomposition but the effects of denoising on material decomposition have not been investigated. In particular, deep learning methods can reduce inherent PCCT image noise without using a system-based or assumed prior noise model. Therefore, the objective of this study was to investigate the effects of image denoising on quantitative material decomposition in the absence of an influence of spatial resolution on feature recognition. Phantoms comprising multiple pure and spatially uniform contrast agent (gadolinium, iodine) and tissue (calcium, water) compositions were imaged by PCCT with four energy thresholds chosen to normalize photon counts and leverage contrast agent k-edges. Image denoising was performed by the established blockmatching and 3D-filtering (BM3D) algorithm or deep learning using convolutional neural networks. Material decomposition was performed on as-acquired, BM3D-denoised, and deep-learning-denoised datasets using constrained maximum likelihood estimation and compared to known material concentrations in the phantom. Image denoising by BM3D and deep learning improved the quantitative accuracy of material concentrations determined by material decomposition compared to ground truth, as measured by the root-mean-squared error. Material classification was not improved by image denoising compared with as-acquired images, suggesting that material decomposition was robust against inherent acquisition noise when feature recognition was not challenged by the system spatial resolution. Deeplearning-denoised images balanced preservation of local detail compared to more aggressive smoothing with BM3D, as measured by line profiles across features.

Proceedings Article | 4 April 2022 Presentation + Paper

Super-fast three-dimensional focused x-ray luminescence computed tomography with a gated photon counter

Yile Fang, Michael Lun, Yibing Zhang, Jeffrey Anker, Ge Wang, Changqing Li

Proceedings Volume 12036, 120360K (2022) https://doi.org/10.1117/12.2613157

KEYWORDS: Photon counting, Imaging systems, Data acquisition, X-rays, Oscilloscopes, X-ray imaging, Luminescence, Computed tomography

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Proceedings Article | 9 September 2021 Presentation + Paper

High-resolution interior tomography with a deep neural network trained on a low-resolution dataset

Mengzhou Li, Wenxiang Cong, Ge Wang

Proceedings Volume 11840, 1184018 (2021) https://doi.org/10.1117/12.2594286

KEYWORDS: Lawrencium, Bone, Tomography, Image filtering, Computed tomography, Sensors, Neural networks, Image restoration, CT reconstruction, Signal attenuation

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Proceedings Article | 9 September 2021 Presentation + Paper

Multiple window learning for CT metal artifact reduction

Chuang Niu, Mengzhou Li, Ge Wang

Proceedings Volume 11840, 1184015 (2021) https://doi.org/10.1117/12.2596239

KEYWORDS: Metals, Computed tomography, X-ray computed tomography, Spine, Computer simulations, Visualization, Tissues, Inspection, Image processing, Germanium

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Proceedings Article | 9 September 2021 Open Access

X-ray imaging meets deep learning

Ge Wang

Proceedings Volume 11840, 1184002 (2021) https://doi.org/10.1117/12.2603690

KEYWORDS: X-ray imaging, X-ray computed tomography, Tomography, Neurons, Artificial intelligence, X-rays, Medical imaging, Data modeling, Reconstruction algorithms, Proteins

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Proceedings Article | 9 September 2021 Presentation + Paper

Simultaneous electron density and attenuation coefficient reconstruction: a feasibility study

Christopher Wiedeman, Wenxiang Cong, Ge Wang

Proceedings Volume 11840, 118400D (2021) https://doi.org/10.1117/12.2596280

KEYWORDS: Signal attenuation, Sensors, Photons, Medical imaging, CT reconstruction, Computed tomography, Image restoration, Tomography, Scattering, Image analysis

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SPIE Journal Paper | 18 March 2021 Open Access

Focused x-ray luminescence imaging system for small animals based on a rotary gantry

Michael Lun, Wenxiang Cong, Mohammad Arifuzzaman, Meenakshi Ranasinghe, Sriparna Bhattacharya, Jeffrey Anker, Ge Wang, Changqing Li

JBO, Vol. 26, Issue 03, 036004, (March 2021) https://doi.org/10.1117/12.10.1117/1.JBO.26.3.036004

KEYWORDS: X-rays, X-ray imaging, Luminescence, Imaging systems, Scanners, Reconstruction algorithms, X-ray computed tomography, Tissue optics, Photons, Image restoration

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Significance: The ability to detect and localize specific molecules through tissue is important for elucidating the molecular basis of disease and treatment. Unfortunately, most current molecular imaging tools in tissue either lack high spatial resolution (e.g., diffuse optical fluorescence tomography or positron emission tomography) or lack molecular sensitivity (e.g., micro-computed tomography, μCT). X-ray luminescence imaging emerged about 10 years ago to address this issue by combining the molecular sensitivity of optical probes with the high spatial resolution of x-ray imaging through tissue. In particular, x-ray luminescence computed tomography (XLCT) has been demonstrated as a powerful technique for the high-resolution imaging of deeply embedded contrast agents in three dimensions (3D) for small-animal imaging. Aim: To facilitate the translation of XLCT for small-animal imaging, we have designed and built a small-animal dedicated focused x-ray luminescence tomography (FXLT) scanner with a μCT scanner, synthesized bright and biocompatible nanophosphors as contrast agents, and have developed a deep-learning-based reconstruction algorithm. Approach: The proposed FXLT imaging system was designed using computer-aided design software and built according to specifications. NaGdF4 nanophosphors doped with europium or terbium were synthesized with a silica shell for increased biocompatibility and functionalized with biotin. A deep-learning-based XLCT image reconstruction was also developed based on the residual neural network as a data synthesis method of projection views from few-view data to enhance the reconstructed image quality. Results: We have built the FXLT scanner for small-animal imaging based on a rotational gantry. With all major imaging components mounted, the motor controlling the gantry can be used to rotate the system with a high accuracy. The synthesized nanophosphors displayed distinct x-ray luminescence emission, which enables multi-color imaging, and has successfully been bound to streptavidin-coated substrates. Lastly, numerical simulations using the proposed deep-learning-based reconstruction algorithm has demonstrated a clear enhancement in the reconstructed image quality. Conclusions: The designed FXLT scanner, synthesized nanophosphors, and deep-learning-based reconstruction algorithm show great potential for the high-resolution molecular imaging of small animals.

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Proceedings Article | 16 March 2020 Paper

Multi-task learning for mortality prediction in LDCT images

Hengtao Guo, Melanie Kruger, Ge Wang, Mannudeep Kalra, Pingkun Yan

Proceedings Volume 11314, 113142C (2020) https://doi.org/10.1117/12.2549387

KEYWORDS: Feature extraction, Heart, Neural networks, Network architectures, Lung cancer, Lung, Information visualization, Visualization, Image analysis, Image processing

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Proceedings Article | 28 February 2020 Presentation + Paper

Deep learning based high-resolution reconstruction of trabecular bone microstructures from low-resolution CT scans using GAN-CIRCLE

Indranil Guha, Syed Ahmed Nadeem, Chenyu You, Xiaoliu Zhang, Steven Levy, Ge Wang, James Torner, Punam Saha

Proceedings Volume 11317, 113170U (2020) https://doi.org/10.1117/12.2549318

KEYWORDS: Computed tomography, Bone, X-ray computed tomography, Network architectures, Convolution, CT reconstruction

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Proceedings Article | 25 February 2020 Paper

X-ray luminescence imaging for small animals

Michael Lun, Wenxiang Cong, Md. Arifuzzaman, Meenakshi Ranasinghe, Sriparna Bhattacharya, Jeffrey Anker, Ge Wang, Changqing Li

Proceedings Volume 11224, 112240F (2020) https://doi.org/10.1117/12.2544601

KEYWORDS: X-rays, X-ray imaging, Reconstruction algorithms, Luminescence, Imaging systems, Photons, Near infrared, Scanners, Image restoration

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SPIE Journal Paper | 14 February 2020

Deep adversarial network for super stimulated emission depletion imaging

Mengzhou Li, Hongming Shan, Sergey Pryshchep, Maria Lopez, Ge Wang

JNP, Vol. 14, Issue 01, 016009, (February 2020) https://doi.org/10.1117/12.10.1117/1.JNP.14.016009

KEYWORDS: Stimulated emission depletion microscopy, Image resolution, Point spread functions, Super resolution, Data modeling, Confocal microscopy, Deconvolution, Microscopes, Image enhancement, Microscopy

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Proceedings Article | 11 September 2019 Presentation + Paper

Quadratic neural networks for CT metal artifact reduction

Fenglei Fan, Hongming Shan, Lars Gjesteby, Ge Wang

Proceedings Volume 11113, 111130W (2019) https://doi.org/10.1117/12.2530363

KEYWORDS: Metals, Neurons, Neural networks, Computed tomography, Machine learning, Medical imaging, Network architectures

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Proceedings Article | 10 September 2019 Paper

Low-dose CT simulation with a generative adversarial network

Hongming Shan, Xun Jia, Klaus Mueller, Uwe Kruger, Ge Wang

Proceedings Volume 11113, 111131F (2019) https://doi.org/10.1117/12.2529698

KEYWORDS: X-ray computed tomography, Computed tomography, Denoising, Gallium nitride, Computer programming, Data modeling, Computer simulations, Neural networks, Medical imaging, Germanium

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Proceedings Article | 10 September 2019 Presentation + Paper

Super-resolution MRI and CT through GAN-CIRCLE

Qing Lyu, Chenyu You, Hongming Shan, Yi Zhang, Ge Wang

Proceedings Volume 11113, 111130X (2019) https://doi.org/10.1117/12.2530592

KEYWORDS: Magnetic resonance imaging, Computed tomography, X-ray computed tomography, Super resolution, Image resolution, Neural networks, Scanners, Spatial resolution

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Proceedings Article | 10 September 2019 Paper

Training artificial neurons: an introduction to machine learning

Joshua Goldwag, Ge Wang

Proceedings Volume 11113, 111131P (2019) https://doi.org/10.1117/12.2530718

KEYWORDS: Neurons, Machine learning, Neural networks, Biology, Biomimetics, Medical imaging, Gallium nitride

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Proceedings Article | 10 September 2019 Paper

Machine learning assisted interior phase contrast CT

Ohsung Oh, Ge Wang, Seung Wook Lee

Proceedings Volume 11113, 111131R (2019) https://doi.org/10.1117/12.2530769

KEYWORDS: Phase contrast, Machine learning, Computed tomography, Tissues, Absorption, Signal attenuation, Refraction, Reconstruction algorithms, Algorithm development, Cancer

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Proceedings Article | 10 September 2019 Presentation + Paper

Dual network architecture for few-view CT - trained on ImageNet data and transferred for medical imaging

Huidong Xie, Hongming Shan, Wenxiang Cong, Xiaohua Zhang, Shaohua Liu, Ruola Ning, Ge Wang

Proceedings Volume 11113, 111130V (2019) https://doi.org/10.1117/12.2531198

KEYWORDS: X-ray computed tomography, Network architectures, CT reconstruction, Image filtering, Medical imaging, X-rays, Optical filters, Associative arrays

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Proceedings Article | 10 September 2019 Paper

Systematic analysis of microstructured array anode target for hard x-ray grating interferometer

Guibin Zan, David John Vine, Sylvia J. Y. Lewis, Qiuping Wang, Wenbing Yun, Ge Wang

Proceedings Volume 11113, 111130H (2019) https://doi.org/10.1117/12.2528281

KEYWORDS: Interferometers, X-rays, Hard x-rays, X-ray sources, Absorption, Brain-machine interfaces, X-ray imaging, Monte Carlo methods, Energy efficiency, Phase contrast

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Proceedings Article | 10 September 2019 Paper

Low-dose CT via deep CNN with skip connection and network-in-network

Chenyu You, Linfeng Yang, Yi Zhang, Ge Wang

Proceedings Volume 11113, 111131W (2019) https://doi.org/10.1117/12.2534960

KEYWORDS: Denoising, Image quality, Image processing, Computed tomography, Machine learning, Artificial intelligence

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Proceedings Article | 10 September 2019 Paper

Smoothing L0- and L1-Norm regularizers and their relations to non-local means for CT reconstruction

Yueyang Teng, Qing Guo, Ge Wang

Proceedings Volume 11113, 111131M (2019) https://doi.org/10.1117/12.2530522

KEYWORDS: Expectation maximization algorithms, Compressed sensing, Machine learning, Computed tomography, Detection and tracking algorithms, Image processing, Image quality standards, Neural networks, CT reconstruction, Image quality

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Proceedings Article | 10 September 2019 Paper

Deep-learning-based breast CT for radiation dose reduction

Wenxiang Cong, Hongming Shan, Xiaohua Zhang, Shaohua Liu, Ruola Ning, Ge Wang

Proceedings Volume 11113, 111131L (2019) https://doi.org/10.1117/12.2530234

KEYWORDS: Breast, Computed tomography, X-ray computed tomography, Image restoration, Neural networks, X-rays, Network architectures, Image quality, Data modeling, Convolution

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Proceedings Article | 9 September 2019 Paper

Simultaneous reconstruction of the initial pressure and sound speed in photoacoustic tomography using a deep-learning approach

Hongming Shan, Christopher Wiedeman, Ge Wang, Yang Yang

Proceedings Volume 11105, 1110504 (2019) https://doi.org/10.1117/12.2529984

KEYWORDS: Tissue optics, Acquisition tracking and pointing, Reconstruction algorithms, Acoustics, Ultrasonography, Photoacoustic tomography, Feature extraction, 3D modeling, Thermography, Mathematical modeling

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SPIE Journal Paper | 21 June 2019

Comparison of deep learning and human observer performance for detection and characterization of simulated lesions

Ruben De Man, Grace Gang, Xin Li, Ge Wang

JMI, Vol. 6, Issue 02, 025503, (June 2019) https://doi.org/10.1117/12.10.1117/1.JMI.6.2.025503

KEYWORDS: Signal to noise ratio, Stars, Radiology, Tumors, Java, Convolutional neural networks, Diagnostics, Lithium, Germanium, Image classification

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Proceedings Article | 28 May 2019 Paper

A novel transfer learning framework for low-dose CT

Hongming Shan, Uwe Kruger, Ge Wang

Proceedings Volume 11072, 110722Y (2019) https://doi.org/10.1117/12.2534848

KEYWORDS: Denoising, Computed tomography, Neural networks, Image processing, Machine learning, Medical image reconstruction

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Proceedings Article | 28 May 2019 Paper

Quadratic autoencoder for low-dose CT denoising

Fenglei Fan, Hongming Shan, Ge Wang

Proceedings Volume 11072, 110722Z (2019) https://doi.org/10.1117/12.2534908

KEYWORDS: Neurons, Denoising, Computed tomography, Surgery, Convolution, Machine learning, Feature extraction, Prototyping, Neodymium, Computer programming

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Proceedings Article | 28 May 2019 Paper

Non-uniformity correction for MARS photon-counting detectors

Matthew Getzin, Mengzhou Li, David Rundle, Anthony Butler, Ge Wang

Proceedings Volume 11072, 110722W (2019) https://doi.org/10.1117/12.2534914

KEYWORDS: Sensors, Photodetectors, Nonuniformity corrections, Mars, Data corrections, X-ray detectors, X-ray imaging, Time correlated photon counting, Photon counting

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Proceedings Article | 28 May 2019 Paper

Comparison of deep learning and human observer performance for lesion detection and characterization

Ruben De Man, Grace Gang, Xin Li, Ge Wang

Proceedings Volume 11072, 110721F (2019) https://doi.org/10.1117/12.2532331

KEYWORDS: Convolutional neural networks, Tumors, Signal to noise ratio, Radiology, Diagnostics, Network architectures, Biomedical engineering, Artificial intelligence, Machine learning

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Proceedings Article | 10 May 2019 Paper

Image correction method without gain correction in grating-based x-ray phase-contrast imaging

Guibin Zan, Renfang Hu, Zhao Wu, Qiuping Wang, Wenbing Yun, Ge Wang

Proceedings Volume 11068, 110682A (2019) https://doi.org/10.1117/12.2524694

KEYWORDS: X-rays, X-ray imaging, Sensors, Scattering, Absorption, X-ray detectors, Signal attenuation, Imaging systems, Radiography, Image quality

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Proceedings Article | 1 March 2019 Paper

A directional TV based ring artifact reduction method

Morteza Salehjahromi, Qian Wang, Lars Gjesteby, Dan Harrison, Ge Wang, Hengyong Yu

Proceedings Volume 10948, 109482C (2019) https://doi.org/10.1117/12.2513037

KEYWORDS: Optimization (mathematics), Computed tomography, Image processing, Reconstruction algorithms

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Proceedings Article | 9 March 2018 Presentation + Paper

Metal artifact reduction for radiation therapy: a simulation study

Yannan Jin, Drosoula Giantsoudi, Lin Fu, Joost Verburg, Lars Gjesteby, Ge Wang, Harald Paganetti, Bruno De Man

Proceedings Volume 10573, 105730Q (2018) https://doi.org/10.1117/12.2293840

KEYWORDS: Metals, X-ray computed tomography, Radiotherapy, Sensors, X-rays, Data acquisition, Signal detection, Computer simulations, Computed tomography, Reconstruction algorithms

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SPIE Journal Paper | 8 February 2018

General rigid motion correction for computed tomography imaging based on locally linear embedding

Mianyi Chen, Peng He, Peng Feng, Baodong Liu, Qingsong Yang, Biao Wei, Ge Wang

OE, Vol. 57, Issue 02, 023102, (February 2018) https://doi.org/10.1117/12.10.1117/1.OE.57.2.023102

KEYWORDS: Calibration, Computed tomography, Sensors, 3D image reconstruction, 3D image processing, CT reconstruction, Optical engineering, Reconstruction algorithms, Tomography, Image restoration

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Proceedings Article | 25 September 2017 Presentation + Paper

Deep learning methods for CT image-domain metal artifact reduction

Lars Gjesteby, Qingsong Yang, Yan Xi, Hongming Shan, Bernhard Claus, Yannan Jin, Bruno De Man, Ge Wang

Proceedings Volume 10391, 103910W (2017) https://doi.org/10.1117/12.2274427

KEYWORDS: Computed tomography, Image processing, Radiotherapy, Machine learning, Image quality, Reconstruction algorithms, Convolutional neural networks

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SPIE Journal Paper | 20 September 2017 Open Access

Optical tomographic imaging for breast cancer detection

Wenxiang Cong, Xavier Intes, Ge Wang

JBO, Vol. 22, Issue 09, 096011, (September 2017) https://doi.org/10.1117/12.10.1117/1.JBO.22.9.096011

KEYWORDS: Tumors, Tissues, Absorption, Breast, Image restoration, Breast cancer, Mammography, Optical imaging, Tomography, Tissue optics

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Proceedings Article | 19 September 2017 Presentation + Paper

Numerical study on simultaneous emission and transmission tomography in the MRI framework

Lars Gjesteby, Wenxiang Cong, Ge Wang

Proceedings Volume 10391, 103910F (2017) https://doi.org/10.1117/12.2272505

KEYWORDS: Magnetic resonance imaging, Tomography, Computed tomography, Magnetism, Data acquisition, Imaging systems, Single photon emission computed tomography

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Proceedings Article | 19 September 2017 Presentation + Paper

Deep learning for low-dose CT

Hu Chen, Yi Zhang, Jiliu Zhou, Ge Wang

Proceedings Volume 10391, 103910I (2017) https://doi.org/10.1117/12.2272723

KEYWORDS: X-ray computed tomography, Computed tomography, Computer programming, Reconstruction algorithms, Convolution, Image processing, Deconvolution, Image restoration, CT reconstruction, Image denoising

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Proceedings Article | 9 March 2017 Paper

Deep learning methods to guide CT image reconstruction and reduce metal artifacts

Lars Gjesteby, Qingsong Yang, Yan Xi, Ye Zhou, Junping Zhang, Ge Wang

Proceedings Volume 10132, 101322W (2017) https://doi.org/10.1117/12.2254091

KEYWORDS: Image quality, CT reconstruction, Computed tomography, Metals, Image processing, Error analysis, Reconstruction algorithms, Image restoration, Titanium, Medical imaging

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SPIE Journal Paper | 2 March 2017

New concept on an integrated interior magnetic resonance imaging and medical linear accelerator system for radiation therapy

Xun Jia, Zhen Tian, Yan Xi, Steve Jiang, Ge Wang

JMI, Vol. 4, Issue 01, 015004, (March 2017) https://doi.org/10.1117/12.10.1117/1.JMI.4.1.015004

KEYWORDS: Magnetic resonance imaging, Radiotherapy, Magnetism, Imaging systems, Tumors, Liver, Scanners, Data acquisition, Liver cancer, X-rays

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Proceedings Article | 20 February 2017 Paper

Characteristic performance investigation of a photon counting detector for x-ray fluorescence imaging applications

Liqiang Ren, Muhammad Ghani, Di Wu, Yuhua Li, Wei Chen, Ge Wang, Bin Zheng, Hong Liu

Proceedings Volume 10065, 100650L (2017) https://doi.org/10.1117/12.2253008

KEYWORDS: Photon counting, Sensors, X-ray fluorescence spectroscopy, X-rays, Nanoparticles, Sensor performance, X-ray detectors, X-ray imaging, Luminescence, Calibration, Collimators

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Proceedings Article | 15 February 2017 Paper

New contrasts for x-ray imaging and synergy with optical imaging

Ge Wang

Proceedings Volume 10057, 100570K (2017) https://doi.org/10.1117/12.2261456

KEYWORDS: X-rays, X-ray imaging, Optical imaging, X-ray fluorescence spectroscopy, X-ray optics, Sensors, Tissues, Signal attenuation, Tomography, Luminescence

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Proceedings Article | 21 October 2016 Paper

Innovation and fusion of x-ray and optical tomography for mouse studies of breast cancer

Ge Wang, Wenxiang Cong, Qingsong Yang, Qi Pian, Shouping Zhu, Jimin Liang, Margarida Barroso, Xavier Intes

Proceedings Volume 9967, 99671R (2016) https://doi.org/10.1117/12.2238188

KEYWORDS: X-rays, Imaging systems, X-ray optics, Optical tomography, Breast cancer, X-ray imaging, Tomography, Tissue optics, Receptors, Tumors

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Proceedings Article | 4 October 2016 Presentation + Paper

Interior tomography from differential phase contrast data via Hilbert transform based on spline functions

Qingsong Yang, Wenxiang Cong, Ge Wang

Proceedings Volume 9967, 996709 (2016) https://doi.org/10.1117/12.2237818

KEYWORDS: Phase contrast, X-ray imaging, X-rays, Tomography, Reconstruction algorithms, X-ray technology, Medicine, Biology, X-ray computed tomography, Physics

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Proceedings Article | 3 October 2016 Presentation + Paper

X-ray interior tensor tomography with 2D gratings

Mianyi Chen, Qingsong Yang, Wenxiang Cong, Biao Wei, Ge Wang

Proceedings Volume 9967, 99670Y (2016) https://doi.org/10.1117/12.2238408

KEYWORDS: Scattering, Tomography, X-rays, X-ray imaging, Laser scattering, 3D image reconstruction, Imaging systems, Phase contrast, Reconstruction algorithms, Sensors

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Proceedings Article | 3 October 2016 Paper

Dictionary learning-based CT detection of pulmonary nodules

Panpan Wu, Kewen Xia, Yanbo Zhang, Xiaohua Qian, Ge Wang, Hengyong Yu

Proceedings Volume 9967, 99671S (2016) https://doi.org/10.1117/12.2236780

KEYWORDS: Associative arrays, Databases, Feature extraction, Lung, Image segmentation, Computed tomography, Chemical species, Actinium, Technetium, CAD systems

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Proceedings Article | 20 September 2016 Presentation + Paper

Enhancing spatial resolution for spectral uCT with aperture encoding

Matthew Getzin, Tianyu Liu, Qingsong Yang, Mianyi Chen, Wenxiang Cong, George Xu, Ge Wang

Proceedings Volume 9967, 99670W (2016) https://doi.org/10.1117/12.2237840

KEYWORDS: Absorption, Image resolution, Resolution enhancement technologies, Computer programming, X-ray imaging, Sensors, X-rays, Monte Carlo methods, Digital filtering, Image filtering

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SPIE Journal Paper | 3 November 2014

Fast and accurate computation of system matrix for area integral model-based algebraic reconstruction technique

Shunli Zhang, Dinghua Zhang, Hao Gong, Omid Ghasemalizadeh, Ge Wang, Guohua Cao

OE, Vol. 53, Issue 11, 113101, (November 2014) https://doi.org/10.1117/12.10.1117/1.OE.53.11.113101

KEYWORDS: Reconstruction algorithms, Computing systems, Sensors, Image quality, Projection systems, Optical engineering, Computed tomography, Model-based design, Image restoration, Iterative methods

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Proceedings Article | 13 September 2014 Paper

Image reconstruction for x-ray K-edge imaging with a photon counting detector

Bo Meng, Wenxiang Cong, Yan Xi, Ge Wang

Proceedings Volume 9212, 921219 (2014) https://doi.org/10.1117/12.2061392

KEYWORDS: Tissues, Signal attenuation, X-rays, Sensors, Gadolinium, X-ray imaging, Photon counting, Image restoration, X-ray detectors, Numerical simulations

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Proceedings Article | 13 September 2014 Paper

Carotid plaque characterization using CT and MRI scans for synergistic image analysis

Matthew Getzin, Yiqin Xu, Arhant Rao, Saaussan Madi, Ali Bahadur, Michelle Lennartz, Ge Wang

Proceedings Volume 9212, 92121B (2014) https://doi.org/10.1117/12.2062144

KEYWORDS: Magnetic resonance imaging, Computed tomography, Tissues, Image registration, Image analysis, Image segmentation, Control systems, Heart, X-ray computed tomography, X-rays

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Proceedings Article | 12 September 2014 Paper

Second order x-ray in-line phase-contrast imaging

Wenxiang Cong, Ge Wang

Proceedings Volume 9212, 92120T (2014) https://doi.org/10.1117/12.2062077

KEYWORDS: X-rays, X-ray imaging, Phase shifts, Tissues, Signal attenuation, Phase contrast, Image restoration, Near field diffraction, Scattering, Phase imaging

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Proceedings Article | 11 September 2014 Paper

Dictionary learning based low-dose x-ray CT reconstruction using a balancing principle

Xuanqin Mou, Junfeng Wu, Ti Bai, Qiong Xu, Hengyong Yu, Ge Wang

Proceedings Volume 9212, 921207 (2014) https://doi.org/10.1117/12.2065459

KEYWORDS: Associative arrays, Reconstruction algorithms, Photons, X-rays, CT reconstruction, Image quality, Chest, X-ray imaging, X-ray computed tomography, Sensors

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Proceedings Article | 11 September 2014 Paper

Total variation minimization-based multimodality medical image reconstruction

Xuelin Cui, Hengyong Yu, Ge Wang, Lamine Mili

Proceedings Volume 9212, 92121D (2014) https://doi.org/10.1117/12.2062602

KEYWORDS: Magnetic resonance imaging, Computed tomography, X-ray computed tomography, Image restoration, Scanners, CT reconstruction, Imaging systems, Fourier transforms, Medical image reconstruction, Medical imaging

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SPIE Journal Paper | 2 July 2014 Open Access

X-ray micromodulated luminescence tomography in dual-cone geometry

Wenxiang Cong, Zhengwei Pan, Robert Filkins, Alok Srivastava, A. Nadeem Ishaque, Plamen Stefanov, Ge Wang

JBO, Vol. 19, Issue 07, 076002, (July 2014) https://doi.org/10.1117/12.10.1117/1.JBO.19.7.076002

KEYWORDS: X-rays, Luminescence, Tomography, Near infrared, Image restoration, X-ray imaging, X-ray optics, X-ray sources, Spatial resolution, Electron multiplying charge coupled devices

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Proceedings Article | 19 March 2014 Paper

Rotating and semi-stationary multi-beamline architecture study for cardiac CT imaging

Jiao Wang, Paul Fitzgerald, Hewei Gao, Yannan Jin, Ge Wang, Bruno De Man

Proceedings Volume 9033, 90335Q (2014) https://doi.org/10.1117/12.2043680

KEYWORDS: Sensors, Radon, Temporal resolution, Computed tomography, Data acquisition, Imaging systems, Reconstruction algorithms, Heart, Cardiac imaging, Image quality

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Proceedings Article | 17 February 2014 Paper

Comparison of lp-regularization-based reconstruction methods for time domain fluorescence molecular tomography on early time gates

Lingling Zhao, He Yang, Wenxiang Cong, Ge Wang, Xavier Intes

Proceedings Volume 8937, 89370V (2014) https://doi.org/10.1117/12.2038662

KEYWORDS: Luminescence, Tomography, Monte Carlo methods, Spatial resolution, Reconstruction algorithms, Fluorescence tomography, Inverse problems, Kidney, 3D modeling, Data modeling

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Proceedings Article | 17 February 2014 Paper

High resolution 3D image reconstruction in laminar optical tomography based on compressive sensing

Fugang Yang, Mehmet Ozturk, Wenxiang Cong, Ge Wang, Xavier Intes

Proceedings Volume 8937, 89370R (2014) https://doi.org/10.1117/12.2037890

KEYWORDS: Inverse problems, Optical tomography, Compressed sensing, Data modeling, Image resolution, Image restoration, Luminescence, Monte Carlo methods, Sensors, 3D image reconstruction

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Proceedings Article | 28 September 2013 Paper

Spectrography for 3D analysis from a single spectral view

Yan Xi, Jun Zhao, Xiaojing Huang, Hengyong Yu, Yuxin Wang, Ge Wang

Proceedings Volume 8845, 88450I (2013) https://doi.org/10.1117/12.2023464

KEYWORDS: X-rays, Optical spheres, Sensors, Diffraction, Free electron lasers, Numerical simulations, Signal detection, X-ray imaging, Fourier transforms, Reconstruction algorithms

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Proceedings Article | 17 October 2012 Paper

Stereo-imaging towards spectrography for 3D analysis from a single spectral view

Yan Xi, Ge Wang, Hengyong Yu, Yuxin Wang, Jun Zhao

Proceedings Volume 8506, 85061X (2012) https://doi.org/10.1117/12.934819

KEYWORDS: X-rays, Diffraction, Optical spheres, X-ray diffraction, Reconstruction algorithms, X-ray imaging, X-ray detectors, Sensors, Signal to noise ratio, Associative arrays

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Proceedings Article | 17 October 2012 Paper

High order total variation method for interior tomography

Jiansheng Yang, Hengyong Yu, Wenxiang Cong, Ming Jiang, Ge Wang

Proceedings Volume 8506, 85061B (2012) https://doi.org/10.1117/12.929123

KEYWORDS: Tomography, X-rays, Single photon emission computed tomography, Reconstruction algorithms, X-ray computed tomography, Biomedical optics, Algorithm development, Distributed interactive simulations, Signal attenuation, X-ray imaging

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Proceedings Article | 17 October 2012 Paper

An RIP-based evaluation method for candidate next generation cardiac CT architectures with carbon nanotube x-ray source

Baodong Liu, Ge Wang, Bruno De Man, Elizabeth Krupinski, Hengyong Yu

Proceedings Volume 8506, 850610 (2012) https://doi.org/10.1117/12.928665

KEYWORDS: X-ray sources, Sensors, X-ray computed tomography, X-rays, Imaging systems, Composites, Carbon nanotubes, Temporal resolution, Computed tomography, Reconstruction algorithms

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Proceedings Article | 17 October 2012 Paper

Orthogonal-rotating tetrahedral scanning for cone-beam CT

Ivan Ye, Ge Wang

Proceedings Volume 8506, 850611 (2012) https://doi.org/10.1117/12.929179

KEYWORDS: X-ray sources, Optical spheres, X-ray computed tomography, X-rays, Spherical lenses, Sensors, Video, Data acquisition, Solids, Tomography

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Proceedings Article | 17 October 2012 Paper

Spectrography: volumetric reconstruction from one or two spectral views

Hengyong Yu, Ge Wang

Proceedings Volume 8506, 85061Y (2012) https://doi.org/10.1117/12.939471

KEYWORDS: X-rays, Optical spheres, 3D modeling, Sensors, Phase retrieval, Algorithm development, X-ray imaging, Optimization (mathematics), Fourier transforms, Reconstruction algorithms

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Proceedings Article | 17 October 2012 Paper

A new CT architecture with stationary x-ray sources

Guohua Cao, Baodong Liu, Hengyong Yu, Ge Wang

Proceedings Volume 8506, 850613 (2012) https://doi.org/10.1117/12.930571

KEYWORDS: Temporal resolution, Sensors, X-ray sources, X-rays, X-ray computed tomography, Tomography, Reconstruction algorithms, X-ray detectors, Data acquisition, Computed tomography

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Proceedings Article | 17 October 2012 Paper

Unified dual-modality image reconstruction with dual dictionaries

Yang Lu, Jun Zhao, Tiange Zhuang, Ge Wang

Proceedings Volume 8506, 85061V (2012) https://doi.org/10.1117/12.932246

KEYWORDS: Magnetic resonance imaging, Computed tomography, Associative arrays, Image restoration, X-ray computed tomography, Image quality, Reconstruction algorithms, CT reconstruction, Positron emission tomography, Tissues

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SPIE Journal Paper | 6 August 2012 Open Access

Tetrahedron-based orthogonal simultaneous scan for cone-beam computed tomography

Ivan Ye, Ge Wang

OE, Vol. 51, Issue 8, 080502, (August 2012) https://doi.org/10.1117/12.10.1117/1.OE.51.8.080502

KEYWORDS: X-ray sources, Spherical lenses, X-rays, Computed tomography, X-ray computed tomography, Sensors, Video, Data acquisition, Optical spheres, Optical engineering

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SPIE Journal Paper | 4 June 2012 Open Access

Scanning-fiber-based imaging method for tissue engineering

Matthias Hofmann, Bryce Whited, Josh Mitchell, William Vogt, Tracy Criswell, Christopher Rylander, Marissa Rylander, Shay Soker, Ge Wang, Yong Xu

JBO, Vol. 17, Issue 06, 066010, (June 2012) https://doi.org/10.1117/12.10.1117/1.JBO.17.6.066010

KEYWORDS: Luminescence, Image resolution, Skin, Imaging systems, Tissue engineering, Signal to noise ratio, Scattering, Tissues, Tissue optics, Micromirrors

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SPIE Journal Paper | 1 July 2011 Open Access

Monte Carlo fluorescence microtomography

Alexander Cong, Wenxiang Cong, Ge Wang, Matthias Hofmann, Yong Xu

JBO, Vol. 16, Issue 07, 070501, (July 2011) https://doi.org/10.1117/12.10.1117/1.3596171

KEYWORDS: Luminescence, Monte Carlo methods, Tissue optics, Light scattering, Scattering, Microscopy, Spatial resolution, Tomography, Tissues, Biomedical optics

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SPIE Journal Paper | 1 June 2011 Open Access

Spectrally resolving and scattering-compensated x-ray luminescence/fluorescence computed tomography

Wenxiang Cong, Haiou Shen, Ge Wang

JBO, Vol. 16, Issue 06, 066014, (June 2011) https://doi.org/10.1117/12.10.1117/1.3592499

KEYWORDS: X-rays, Near infrared, Scattering, Photons, Computed tomography, Laser scattering, Luminescence, X-ray imaging, X-ray fluorescence spectroscopy, Light scattering

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Proceedings Article | 3 March 2011 Paper

Interior tomography from low-count local projections and associated Hilbert transform data

Qiong Xu, Hengyong Yu, Xuanqin Mou, Ge Wang

Proceedings Volume 7961, 796130 (2011) https://doi.org/10.1117/12.877901

KEYWORDS: Tomography, Sensors, Optimization (mathematics), Compressed sensing, Computed tomography, Numerical simulations, CT reconstruction, X-ray sources, Signal attenuation, Gold

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Proceedings Article | 10 February 2011 Paper

Fully parallel adaptive finite element simulation using the simplified spherical harmonics approximations for frequency-domain fluorescence-enhanced optical imaging

Yujie Lu, Banghe Zhu, Haiou Shen, John Rasmussen, Ge Wang, Eva Sevick-Muraca

Proceedings Volume 7892, 78920F (2011) https://doi.org/10.1117/12.873587

KEYWORDS: Monte Carlo methods, Photon transport, Chemical elements, Computer simulations, Phase shifts, Spherical lenses, Optical imaging, Reconstruction algorithms, Luminescence, Finite element methods

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Proceedings Article | 20 September 2010 Paper

Overview of multisource CT systems and methods

Jun Zhao, Yang Lu, Tiange Zhuang, Ge Wang

Proceedings Volume 7804, 78040H (2010) https://doi.org/10.1117/12.860307

KEYWORDS: Reconstruction algorithms, X-ray computed tomography, Temporal resolution, X-rays, Algorithm development, Tomography, Sensors, Detection and tracking algorithms, X-ray sources, Imaging systems

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Proceedings Article | 20 September 2010 Paper

Recent progress in local reconstruction

Hengyong Yu, Qiong Xu, Xuanqin Mou, Ge Wang

Proceedings Volume 7804, 78040V (2010) https://doi.org/10.1117/12.859772

KEYWORDS: Tomography, Reconstruction algorithms, Computed tomography, CT reconstruction, X-ray computed tomography, X-rays, Image quality, Image filtering, Atrial fibrillation, Image resolution

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Proceedings Article | 2 September 2010 Paper

Statistical interior tomography

Qiong Xu, Hengyong Yu, Xuanqin Mou, Ge Wang

Proceedings Volume 7804, 78041I (2010) https://doi.org/10.1117/12.860362

KEYWORDS: Tomography, Reconstruction algorithms, Photons, Spatial resolution, Signal attenuation, Data modeling, Image quality, Numerical simulations, Sensors, Compressed sensing

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SPIE Journal Paper | 1 June 2010

Experimental measurement of human head motion for high-resolution computed tomography system design

Liang Li, Zhiqiang Chen, Xin Jin, Hengyong Yu, Ge Wang

OE, Vol. 49, Issue 06, 063201, (June 2010) https://doi.org/10.1117/12.10.1117/1.3454379

KEYWORDS: Head, Computed tomography, Motion measurement, Cameras, Imaging systems, Computing systems, In vivo imaging, X-ray computed tomography, Optical engineering, Lithium

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Proceedings Article | 22 May 2009 Paper

Multiscale 3D bioimaging: from cell, tissue to whole organism

S. Lau, Ge Wang, Margam Chandrasekeran, Victor Fan, Mohd Nazrul, Hauyee Chang, Tiffany Fong, Jeff Gelb, Michael Feser, Wenbing Yun

Proceedings Volume 7378, 73781V (2009) https://doi.org/10.1117/12.828043

KEYWORDS: Tissues, Image resolution, Bone, X-rays, Tissue optics, 3D image processing, X-ray computed tomography, Tomography, Organisms, Cartilage

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While electron microscopes and AFMs are capable of high resolution imaging to molecular levels, there is an ongoing problem in integrating these results into the larger scale structure and functions of tissue and organs within a complex organism. Imaging biological samples with optical microscopy is predominantly done with histology and immunohistochemistry, which can take up to a several weeks to prepare, are artifact prone and only available as individual 2D images. At the nano resolution scale, the higher resolution electron microscopy and AFM are used, but again these require destructive sample preparation and data are in 2D. To bridge this gap, we describe a rapid non invasive hierarchical bioimaging technique using a novel lab based x-ray computed tomography to characterize complex biological organism in multiscale- from whole organ (mesoscale) to calcified and soft tissue (microscale), to subcellular structures, nanomaterials and cellular-scaffold interaction (nanoscale). While MicroCT (micro x-ray computed tomography) is gaining in popularity for non invasive bones and tissue imaging, contrast and resolution are still vastly inadequate compared to histology. In this study we will present multiscale results from a novel microCT and nanoCT (nano x-ray tomography system). The novel MicroCT can image large specimen and tissue sample at histology resolution of submicron voxel resolution, often without contrast agents, while the nanoCT using x-ray optics similar to those used in synchrotron radiation facilities, has 20nm voxel resolution, suitable for studying cellular, subcellular morphology and nanomaterials. Multiscale examples involving both calcified and soft tissue will be illustrated, which include imaging a rat tibia to the individual channels of osteocyte canaliculli and lacunae and an unstained whole murine lung to its alveoli. The role of the novel CT will also be discussed as a possible means for rapid virtual histology using a biopsy of a human regenerated bone sample done without contrast agents and that of other soft tissues with contrast agents. Comparison between histology, SEM and MRI will be given.

Proceedings Article | 14 March 2009 Paper

Exact and stable interior ROI reconstruction for radial MRI

Jie Zhang, Hengyong Yu, Curt Corum, Michael Garwood, Ge Wang

Proceedings Volume 7258, 72585G (2009) https://doi.org/10.1117/12.812035

KEYWORDS: Magnetic resonance imaging, Tomography, Temporal resolution, Spatial resolution, Data acquisition, Digital filtering, Numerical simulations, Computed tomography, Image restoration, Magnetism

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Proceedings Article | 16 September 2008 Paper

X-ray phase-contrast imaging with 2D grating interferometry

Ming Jiang, Christopher Lee Wyatt, Ge Wang

Proceedings Volume 7078, 707816 (2008) https://doi.org/10.1117/12.794069

KEYWORDS: X-rays, X-ray imaging, Interferometry, Gaussian beams, Phase measurement, Phase shifts, Fringe analysis, Spatial coherence, Imaging systems, Phase shift keying

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Proceedings Article | 15 September 2008 Paper

Investigation of helix-saddle trajectories for cone-beam CT

Yang Lu, Jun Zhao, Erwei Bai, Ge Wang

Proceedings Volume 7078, 70780I (2008) https://doi.org/10.1117/12.793728

KEYWORDS: Sensors, Computed tomography, Reconstruction algorithms, Angiography, Algorithm development, Detection and tracking algorithms, Biomedical engineering, Control systems, Spherical lenses, Lutetium

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Proceedings Article | 15 September 2008 Paper

Determination of the exact reconstruction region in the cone-beam composite-circling mode

Lena Ye, Hengyong Yu, Ge Wang

Proceedings Volume 7078, 70780J (2008) https://doi.org/10.1117/12.791284

KEYWORDS: Composites, Optical spheres, X-rays, Reconstruction algorithms, X-ray computed tomography, X-ray sources, Algorithm development, Scanners, Image restoration, Tomography

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Proceedings Article | 15 September 2008 Paper

Interior tomography: theory, algorithms and applications

Hengyong Yu, Yangbo Ye, Ge Wang

Proceedings Volume 7078, 70780F (2008) https://doi.org/10.1117/12.794981

KEYWORDS: Tomography, Reconstruction algorithms, Algorithm development, Algorithms, X-ray computed tomography, Blood, X-rays, Numerical simulations, Photovoltaics, Computed tomography

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Proceedings Article | 15 September 2008 Paper

Exact image reconstruction for triple-source cone-beam CT along saddle trajectories

Yang Lu, Jun Zhao, Ge Wang

Proceedings Volume 7078, 70780K (2008) https://doi.org/10.1117/12.793716

KEYWORDS: X-ray computed tomography, Sensors, Reconstruction algorithms, Temporal resolution, Image quality, Arteries, Scanners, Heart, Image restoration, X-ray sources

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Proceedings Article | 18 March 2008 Paper

Parameter optimization for a grating-based phase contrast x-ray system

Bonsung Koo, Ming Jiang, Christopher Wyatt, Ge Wang

Proceedings Volume 6913, 691348 (2008) https://doi.org/10.1117/12.770548

KEYWORDS: Phase contrast, X-rays, Spatial resolution, Tissues, X-ray imaging, X-ray sources, Interferometers, Phase shifts, Signal attenuation, Sensors

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SPIE Journal Paper | 1 March 2008 Open Access

Integral equations of the photon fluence rate and flux based on a generalized Delta-Eddington phase function

Wenxiang Cong, Haiou Shen, Alex Cong, Ge Wang

JBO, Vol. 13, Issue 02, 024016, (March 2008) https://doi.org/10.1117/12.10.1117/1.2907168

KEYWORDS: Scattering, Biomedical optics, Tissue optics, Photon transport, Absorption, Anisotropy, Light scattering, Sensors, Computer simulations, Monte Carlo methods

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Proceedings Article | 13 March 2007 Paper

3D bioluminescent source localization of different depths with spectrum information and adaptive finite element analysis

Yujie Lv, Jie Tian, Wenxiang Cong, Ge Wang, Wei Yang, Min Xu

Proceedings Volume 6510, 651025 (2007) https://doi.org/10.1117/12.709018

KEYWORDS: Reconstruction algorithms, Monte Carlo methods, Tomography, Algorithm development, Diffusion, Finite element methods, Bioluminescence, Source localization, Biomedical optics, Error analysis

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