Dr. Bo Ning Profile

Dr. Bo Ning

R&D Staff Engineer at Children's National Hospital

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Publications (5)

SPIE Journal Paper | 28 November 2022 Open Access

Unsupervised and quantitative intestinal ischemia detection using conditional adversarial network in multimodal optical imaging

Yaning Wang, Laura Tiusaba, Shimon Jacobs, Michele Saruwatari, Bo Ning, Marc Levitt, Anthony Sandler, So-Hyun Nam, Jin Kang, Jaepyeong Cha

JMI, Vol. 9, Issue 06, 064502, (November 2022) https://doi.org/10.1117/12.10.1117/1.JMI.9.6.064502

KEYWORDS: RGB color model, Laser speckle contrast imaging, Ischemia, Image registration, Surgery, Tissues, Data modeling, Education and training, Speckle, Gallium nitride

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PurposeIntraoperative evaluation of bowel perfusion is currently dependent upon subjective assessment. Thus, quantitative and objective methods of bowel viability in intestinal anastomosis are scarce. To address this clinical need, a conditional adversarial network is used to analyze the data from laser speckle contrast imaging (LSCI) paired with a visible-light camera to identify abnormal tissue perfusion regions.ApproachOur vision platform was based on a dual-modality bench-top imaging system with red-green-blue (RGB) and dye-free LSCI channels. Swine model studies were conducted to collect data on bowel mesenteric vascular structures with normal/abnormal microvascular perfusion to construct the control or experimental group. Subsequently, a deep-learning model based on a conditional generative adversarial network (cGAN) was utilized to perform dual-modality image alignment and learn the distribution of normal datasets for training. Thereafter, abnormal datasets were fed into the predictive model for testing. Ischemic bowel regions could be detected by monitoring the erroneous reconstruction from the latent space. The main advantage is that it is unsupervised and does not require subjective manual annotations. Compared with the conventional qualitative LSCI technique, it provides well-defined segmentation results for different levels of ischemia.ResultsWe demonstrated that our model could accurately segment the ischemic intestine images, with a Dice coefficient and accuracy of 90.77% and 93.06%, respectively, in 2560 RGB/LSCI image pairs. The ground truth was labeled by multiple and independent estimations, combining the surgeons’ annotations with fastest gradient descent in suspicious areas of vascular images. The total processing time was 0.05 s for an image size of 256 × 256.ConclusionsThe proposed cGAN can provide pixel-wise and dye-free quantitative analysis of intestinal perfusion, which is an ideal supplement to the traditional LSCI technique. It has potential to help surgeons increase the accuracy of intraoperative diagnosis and improve clinical outcomes of mesenteric ischemia and other gastrointestinal surgeries.

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Proceedings Article | 9 March 2022 Presentation + Paper

Computer-aided detection of parathyroid glands using a dual-RGB/NIR imaging and deep learning technique

Jongchan Kim, Jennifer Yoo, Yoseph Kim, Eugene Oh, Bo Ning, Jonathon Russell, Jaepyeong Cha

Proceedings Volume 11935, 1193504 (2022) https://doi.org/10.1117/12.2608939

KEYWORDS: RGB color model, Data modeling, Performance modeling, Surgery, Near infrared, Computer-aided diagnosis, Computer aided diagnosis and therapy, Imaging systems, Visual process modeling

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Proceedings Article | 21 February 2020 Paper

Development of a portable imager for intraoperative real-time localization of parathyroid glands

Eugene Oh, Wan Wook Kim, So-Hyun Nam, Gyeong Woo Cheon, Bo Ning, Jaepyeong Cha

Proceedings Volume 11229, 1122907 (2020) https://doi.org/10.1117/12.2546250

KEYWORDS: Imaging systems, Surgery, Laser speckle contrast imaging, Near infrared, Tissues, Kidney, RGB color model, Visualization, Blood circulation, Luminescence

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Proceedings Article | 19 April 2017 Presentation + Paper

Photoacoustic microscopy of cerebral hemodynamic and oxygen-metabolic responses to anesthetics

Rui Cao, Jun Li, Bo Ning, Naidi Sun, Tianxiong Wang, Zhiyi Zuo, Song Hu

Proceedings Volume 10051, 100510V (2017) https://doi.org/10.1117/12.2251684

KEYWORDS: Hypoxia, Pre-clinical research, Head, Hemodynamics, Photoacoustic microscopy, Oxygen, Brain, Blood circulation, Mode conditioning cables, Neuroimaging

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SPIE Journal Paper | 30 November 2016 Open Access

Multiparametric photoacoustic microscopy of the mouse brain with 300-kHz A-line rate

Tianxiong Wang, Naidi Sun, Rui Cao, Bo Ning, Ruimin Chen, Qifa Zhou, Song Hu

NPh, Vol. 3, Issue 04, 045006, (November 2016) https://doi.org/10.1117/12.10.1117/1.NPh.3.4.045006

KEYWORDS: Brain, Photoacoustic microscopy, Acoustics, Hybrid optics, In vivo imaging, Oxygen, Laser optics, Neuroimaging, Raman spectroscopy, Single mode fibers

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