Prof. Martin G. Wagner Profile

Prof. Martin G. Wagner

Assistant Professor at Univ of Wisconsin Madison

SPIE Involvement:

Author

Publications (26)

Proceedings Article | 1 April 2024 Presentation + Paper

A study on the influence of radiation dose on device tracking accuracy during continuous-sweep limited angle fluoroscopy

Martin Wagner, Paul Laeseke, Amish Raval, Michael Speidel

Proceedings Volume 12925, 129251S (2024) https://doi.org/10.1117/12.3006311

KEYWORDS: Image segmentation, Fluoroscopy, 3D projection, 3D modeling, 3D acquisition, Sensors, X-rays, 3D tracking, X-ray imaging, 3D image reconstruction

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Proceedings Article | 1 April 2024 Poster + Paper

Comparison of model-based iterative vs non-iterative 3D device reconstruction for continuous-sweep limited-angle fluoroscopy

Martin Wagner, Ayca Kutlu, Brian Davis, Paul Laeseke, Amish Raval, Michael Speidel

Proceedings Volume 12925, 129253U (2024) https://doi.org/10.1117/12.3006315

KEYWORDS: 3D modeling, Image segmentation, Reconstruction algorithms, Instrument modeling, 3D image reconstruction, Model based design, 3D equipment, Fluoroscopy, Cone beam computed tomography, 3D projection

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Proceedings Article | 1 April 2024 Presentation + Paper

FEM deformable liver registration to facilitate CBCT guided histotripsy

Grace Minesinger, Paul Laeseke, Ayca Kutlu, Michael Speidel, Martin Wagner

Proceedings Volume 12925, 129251T (2024) https://doi.org/10.1117/12.3006515

KEYWORDS: Liver, Image segmentation, Cone beam computed tomography, Finite element methods, Image registration, Deformation, Motion models, Blood vessels

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SPIE Journal Paper | 4 January 2024

Motion-compensation approach for quantitative digital subtraction angiography and its effect on in-vivo blood velocity measurement

Joseph Whitehead, Sarvesh Periyasamy, Paul Laeseke, Michael Speidel, Martin Wagner

JMI, Vol. 11, Issue 01, 013501, (January 2024) https://doi.org/10.1117/12.10.1117/1.JMI.11.1.013501

KEYWORDS: Blood, Image segmentation, Velocity measurements, Angiography, Image registration, Arteries, Motion measurement, Motion analysis, In vivo imaging, Linear regression

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Proceedings Article | 7 April 2023 Presentation + Paper

A histotripsy targeting approach using a mobile C-arm

Martin Wagner, Paul Laeseke, Ayca Kutlu, Grace Minesinger, Sarvesh Periyasamy, Michael Speidel

Proceedings Volume 12463, 124630O (2023) https://doi.org/10.1117/12.2654002

KEYWORDS: Calibration, Cone beam computed tomography, Robotics, Transducers, Ultrasonography, Tumors, Pose estimation, 3D acquisition, Ultrasound transducers, Image segmentation

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Proceedings Article | 3 April 2023 Presentation + Paper

Dynamic 3D imaging of contrast medium flow on an interventional C-arm using a pulsed injection protocol

Erick Oberstar, Martin Wagner, Mariya Pravdivtseva, Jingfeng Jiang, Michael Speidel

Proceedings Volume 12466, 124660U (2023) https://doi.org/10.1117/12.2654368

KEYWORDS: Aneurysms, X-rays, Magnetic resonance imaging, X-ray imaging, Image restoration, 3D image reconstruction, Blood circulation, 3D image processing, Contrast agents

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Proceedings Article | 4 April 2022 Presentation + Paper

Dual-energy image noise reduction on an interventional x-ray system

Ethan Nikolau, Joseph Whitehead, Martin Wagner, Paul Laeseke, Michael Speidel

Proceedings Volume 12031, 1203112 (2022) https://doi.org/10.1117/12.2612259

KEYWORDS: Denoising, Tissues, Iodine, Image filtering, Angiography, Visualization, Chest, X-rays, Linear filtering, Image processing

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Proceedings Article | 4 April 2022 Presentation + Paper

A motion compensated approach to quantitative digital subtraction angiography

Joseph Whitehead, Carson Hoffman, Sarvesh Periyasamy, Paul Laeseke, Michael Speidel, Martin Wagner

Proceedings Volume 12031, 120311L (2022) https://doi.org/10.1117/12.2611816

KEYWORDS: Image segmentation, Angiography, Image registration, Blood, Motion measurement, Arteries, Velocity measurements, Blood circulation, Iodine, In vivo imaging

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Proceedings Article | 4 April 2022 Presentation + Paper

Continuous-sweep limited angle fluoroscopy guidance for percutaneous needle procedures

Martin Wagner, Sarvesh Periyasamy, Joseph Whitehead, Paul Laeseke, Michael Speidel

Proceedings Volume 12034, 120341B (2022) https://doi.org/10.1117/12.2611571

KEYWORDS: Image segmentation, 3D modeling, Fluoroscopy, 3D acquisition, Lung, 3D image processing, X-ray computed tomography, Biopsy, Data modeling, Visualization

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SPIE Journal Paper | 15 October 2021

Three-dimensional catheter navigation of airways using continuous-sweep limited angle fluoroscopy on a C-arm

Martin Wagner, Sarvesh Periyasamy, Sebastian Schafer, Paul Laeseke, Michael Speidel

JMI, Vol. 8, Issue 05, 055001, (October 2021) https://doi.org/10.1117/12.10.1117/1.JMI.8.5.055001

KEYWORDS: Image segmentation, Fluoroscopy, X-rays, 3D modeling, X-ray imaging, 3D image processing, 3D acquisition, Navigation systems, Gold, Instrument modeling

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Proceedings Article | 15 February 2021 Presentation + Paper

Method for 3D navigation of airways on a single C-arm using multi-sweep limited angle acquisition and frame-by-frame device reconstruction

Martin Wagner, Sarvesh Periyasamy, Sebastian Schafer, Paul Laeseke, Michael Speidel

Proceedings Volume 11598, 115980O (2021) https://doi.org/10.1117/12.2580957

KEYWORDS: 3D acquisition, X-rays, X-ray imaging, 3D modeling, Tumors, Motion models, Model-based design, Image registration, Image acquisition, Gold

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Proceedings Article | 16 March 2020 Presentation + Paper

Evaluation of real-time guidewire navigation using virtual endoscopic 4D fluoroscopy

Brian Davis, Martin Wagner, Sarvesh Periyasamy, Charles Mistretta, Charles Strother, Paul Laeseke, Michael Speidel

Proceedings Volume 11315, 1131515 (2020) https://doi.org/10.1117/12.2549683

KEYWORDS: Fluoroscopy, Endoscopy, 3D displays, X-rays, Navigation systems, Cameras, Video, Visualization, Image segmentation, X-ray imaging

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Proceedings Article | 16 March 2020 Presentation + Paper

Simulation of hepatic arteries and synthesis of 2D fluoroscopic images for interventional imaging studies

Joseph Whitehead, Ethan Nikolau, Sarvesh Periyasamy, Luis Torres, Paul Laeseke, Michael Speidel, Martin Wagner

Proceedings Volume 11312, 113121W (2020) https://doi.org/10.1117/12.2549570

KEYWORDS: Image segmentation, Arteries, Liver, X-rays, X-ray imaging, Computer simulations, Digital x-ray imaging, Binary data, 3D modeling

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Training of deep learning-based segmentation algorithms requires large datasets of annotated images. Obtaining large clinical datasets, particularly for interventional imaging, is difficult and annotating vessels manually in the images is very time-consuming. Simulated images can be used to supplement clinical datasets. We developed a technique for the simulation of realistic, anatomically- and physiologically-motivated hepatic artery trees and subsequent synthesis of fluoroscopic images. The proposed approach creates a network of main feeding arteries for each of the eight liver segments as defined by the Couinaud classification system. A constrained constructive optimization based approach was then used to connect a set of randomly generated endpoints within each segment to the corresponding feeding artery. Vessel curvature was created using cubic splines and the generated vasculature was inserted into the digital XCAT phantom. The simulated 2D fluoroscopic images were generated using ray tracing and included focal spot blur, detector blur and Poisson noise. The length ratio (1.1 ± 1.7) and two parameters from Murray’s law, branching angles (7.9 ± 7.7^𝑜 mean absolute difference from Murray’s law) and radius ratio (1.0 ± 0.1) of the generated vasculature were in accordance with values reported in literature (1.3, Murray’s law applied to branching angles, and 1.0 respectively). Simulated vasculature included main branches for each of the eight Couinaud segments, where 87% of all connected endpoints terminated in the same segment. Simulated 2D projection images were analyzed using a vessel phantom study with contrast-enhanced tubes (0.305-3.353 mm diameter). The normalized root mean squared difference between the measured and simulated vessel profiles averaged 3.5%. In conclusion, the proposed method provides realistic simulated fluoroscopic images of the liver vasculature and could prove useful for the training of machine learning based algorithms for vessel segmentation.

Proceedings Article | 16 March 2020 Presentation + Paper

Feasibility of 3D motion-compensated needle guidance for TIPS procedures

Martin Wagner, Sarvesh Periyasamy, Michael Speidel, Paul Laeseke

Proceedings Volume 11315, 1131505 (2020) https://doi.org/10.1117/12.2548874

KEYWORDS: Veins, 3D modeling, X-rays, Image segmentation, 3D image processing, Motion models, X-ray imaging, 3D acquisition, Liver, Reconstruction algorithms

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Proceedings Article | 8 March 2019 Paper

Real-time 3D image fusion system for valvular interventions based on echocardiography and biplane x-ray fluoroscopy

Martin Wagner, Lindsay Bodart, Amish Raval, Michael Speidel

Proceedings Volume 10951, 1095121 (2019) https://doi.org/10.1117/12.2512793

KEYWORDS: Ultrasonography, X-rays, X-ray imaging, Image fusion, 3D image processing, 3D modeling, Imaging systems, Image registration, 3D displays, Visualization

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Proceedings Article | 8 March 2019 Paper

Dual-modality phantom for evaluating x-ray/echo registration accuracy

Lindsay Bodart, Timothy Hall, Jacob Ellis, Benjamin Ciske, Martin Wagner, Amish Raval, Michael Speidel

Proceedings Volume 10951, 109511V (2019) https://doi.org/10.1117/12.2512908

KEYWORDS: X-rays, Ultrasonography, Image registration, Fluoroscopy, Heart, Visualization, X-ray imaging

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Proceedings Article | 1 March 2019 Paper

Deep learning based guidewire segmentation in x-ray images

Martin Wagner, Paul Laeseke, Michael Speidel

Proceedings Volume 10948, 1094844 (2019) https://doi.org/10.1117/12.2512820

KEYWORDS: Image segmentation, X-rays, X-ray imaging, Arteries, 3D acquisition, Computer programming, Neural networks, Image processing algorithms and systems, Liver, Tumors

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Proceedings Article | 13 March 2018 Paper

Clinical feasibility of x-ray based pose estimation of a transthoracic echo probe using attached fiducials

Lindsay Bodart, Benjamin Ciske, Martin Wagner, Amish Raval, Michael Speidel

Proceedings Volume 10576, 1057626 (2018) https://doi.org/10.1117/12.2293875

KEYWORDS: 3D modeling, X-rays, Sensors, Transducers, X-ray imaging, Heart, 3D image processing, Acoustics, Ultrasonography, 3D acquisition

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Proceedings Article | 13 March 2018 Presentation + Paper

A real-time system for prosthetic valve tracking

Martin Wagner, Lindsay Bodart, Sebastian Schafer, Amish Raval, Michael Speidel

Proceedings Volume 10576, 105761A (2018) https://doi.org/10.1117/12.2293837

KEYWORDS: 3D modeling, 3D image processing, Heart, Visual process modeling, Visualization, Optical tracking, Real-time computing, Fluoroscopy, Detection and tracking algorithms, Prototyping

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Proceedings Article | 2 March 2018 Presentation + Paper

Feasibility of intra-acquisition motion correction for 4D DSA reconstruction for applications in the thorax and abdomen

Martin Wagner, Paul Laeseke, Colin Harari, Sebastian Schafer, Michael Speidel, Charles Mistretta

Proceedings Volume 10574, 1057415 (2018) https://doi.org/10.1117/12.2293812

KEYWORDS: 3D acquisition, Abdomen, 3D image processing, Reconstruction algorithms, Blood circulation, Image registration, Computed tomography, Vascular diseases, 3D image reconstruction, Radiology

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Proceedings Article | 9 March 2017 Paper

Localization of cardiac volume and patient features in inverse geometry x-ray fluoroscopy

Michael Speidel, Jordan Slagowski, David A. Dunkerley, Martin Wagner, Tobias Funk, Amish Raval

Proceedings Volume 10132, 101325T (2017) https://doi.org/10.1117/12.2254400

KEYWORDS: Angiography, Fluoroscopy, Arteries, Reconstruction algorithms, Lung, X-ray imaging, Cardiology, Heart, X-ray detectors

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Proceedings Article | 3 March 2017 Presentation + Paper

Feature-based respiratory motion tracking in native fluoroscopic sequences for dynamic roadmaps during minimally invasive procedures in the thorax and abdomen

Martin Wagner, Paul Laeseke, Tilman Schubert, Jordan Slagowski, Michael Speidel, Charles Mistretta

Proceedings Volume 10135, 101351H (2017) https://doi.org/10.1117/12.2254148

KEYWORDS: Feature extraction, Fluoroscopy, Image registration, Abdomen, Image contrast enhancement, Image enhancement, Motion models, Edge detection, Error analysis, Image segmentation, Motion estimation, Liver, Detection and tracking algorithms, Process modeling

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Fluoroscopic image guidance for minimally invasive procedures in the thorax and abdomen suffers from respiratory and cardiac motion, which can cause severe subtraction artifacts and inaccurate image guidance. This work proposes novel techniques for respiratory motion tracking in native fluoroscopic images as well as a model based estimation of vessel deformation. This would allow compensation for respiratory motion during the procedure and therefore simplify the workflow for minimally invasive procedures such as liver embolization. The method first establishes dynamic motion models for both the contrast-enhanced vasculature and curvilinear background features based on a native (non-contrast) and a contrast-enhanced image sequence acquired prior to device manipulation, under free breathing conditions. The model of vascular motion is generated by applying the diffeomorphic demons algorithm to an automatic segmentation of the subtraction sequence. The model of curvilinear background features is based on feature tracking in the native sequence. The two models establish the relationship between the respiratory state, which is inferred from curvilinear background features, and the vascular morphology during that same respiratory state. During subsequent fluoroscopy, curvilinear feature detection is applied to determine the appropriate vessel mask to display. The result is a dynamic motioncompensated vessel mask superimposed on the fluoroscopic image. Quantitative evaluation of the proposed methods was performed using a digital 4D CT-phantom (XCAT), which provides realistic human anatomy including sophisticated respiratory and cardiac motion models. Four groups of datasets were generated, where different parameters (cycle length, maximum diaphragm motion and maximum chest expansion) were modified within each image sequence. Each group contains 4 datasets consisting of the initial native and contrast enhanced sequences as well as a sequence, where the respiratory motion is tracked. The respiratory motion tracking error was between 1.00 % and 1.09 %. The estimated dynamic vessel masks yielded a Sørensen-Dice coefficient between 0.94 and 0.96. Finally, the accuracy of the vessel contours was measured in terms of the 99th percentile of the error, which ranged between 0.64 and 0.96 mm. The presented results show that the approach is feasible for respiratory motion tracking and compensation and could therefore considerably improve the workflow of minimally invasive procedures in the thorax and abdomen

Proceedings Article | 21 March 2016 Paper

Guidewire path tracking and segmentation in 2D fluoroscopic time series using device paths from previous frames

Martin Wagner, Charles Strother, Charles Mistretta

Proceedings Volume 9784, 97842B (2016) https://doi.org/10.1117/12.2216540

KEYWORDS: Image segmentation, Image processing algorithms and systems, Detection and tracking algorithms, Fluoroscopy, 3D modeling, Computer programming, Data acquisition, Visualization, Denoising, Reconstruction algorithms, Ridge detection, Image enhancement, Feature extraction

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Proceedings Article | 18 March 2016 Paper

Biplane reconstruction and visualization of virtual endoscopic and fluoroscopic views for interventional device navigation

Martin Wagner, Charles Strother, Sebastian Schafer, Charles Mistretta

Proceedings Volume 9786, 978613 (2016) https://doi.org/10.1117/12.2216538

KEYWORDS: Reconstruction algorithms, Visualization, Endoscopy, Cerebrovascular diseases, Navigation systems, Cameras, Fluoroscopy, Image segmentation, Angiography, Denoising, Glasses, 3D equipment, 3D image processing, 3D image reconstruction

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Biplane fluoroscopic imaging is an important tool for minimally invasive procedures for the treatment of cerebrovascular diseases. However, finding a good working angle for the C-arms of the angiography system as well as navigating based on the 2D projection images can be a difficult task. The purpose of this work is to propose a novel 4D reconstruction algorithm for interventional devices from biplane fluoroscopy images and to propose new techniques for a better visualization of the results. The proposed reconstruction methods binarizes the fluoroscopic images using a dedicated noise reduction algorithm for curvilinear structures and a global thresholding approach. A topology preserving thinning algorithm is then applied and a path search algorithm minimizing the curvature of the device is used to extract the 2D device centerlines. Finally, the 3D device path is reconstructed using epipolar geometry. The point correspondences are determined by a monotonic mapping function that minimizes the reconstruction error. The three dimensional reconstruction of the device path allows the rendering of virtual fluoroscopy images from arbitrary angles as well as 3D visualizations like virtual endoscopic views or glass pipe renderings, where the vessel wall is rendered with a semi-transparent material. This work also proposes a combination of different visualization techniques in order to increase the usability and spatial orientation for the user. A combination of synchronized endoscopic and glass pipe views is proposed, where the virtual endoscopic camera position is determined based on the device tip location as well as the previous camera position using a Kalman filter in order to create a smooth path. Additionally, vessel centerlines are displayed and the path to the target is highlighted. Finally, the virtual endoscopic camera position is also visualized in the glass pipe view to further improve the spatial orientation. The proposed techniques could considerably improve the workflow of minimally invasive procedures for the treatment of cerebrovascular diseases.

Proceedings Article | 18 March 2016 Paper

Dynamic tracking of prosthetic valve motion and deformation from bi-plane x-ray views: feasibility study

Charles Hatt, Martin Wagner, Amish Raval, Michael Speidel

Proceedings Volume 9786, 978604 (2016) https://doi.org/10.1117/12.2216588

KEYWORDS: 3D modeling, X-rays, Visualization, 3D image processing, Image registration, Instrument modeling, Motion models, 3D image reconstruction, Computer simulations, Detection and tracking algorithms, 3D acquisition

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Proceedings Article | 20 March 2015 Paper

Directional denoising and line enhancement for device segmentation in real time fluoroscopic imaging

Martin Wagner, Kevin Royalty, Erick Oberstar, Charles Strother, Charles Mistretta

Proceedings Volume 9413, 94132C (2015) https://doi.org/10.1117/12.2081545

KEYWORDS: Image segmentation, Denoising, Reconstruction algorithms, Wavelets, Real time imaging, Binary data, Angiography, Image quality, Quality measurement, Image processing

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Showing 5 of 26 publications

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