The Experts below are selected from a list of 73398 Experts worldwide ranked by ideXlab platform
Jin U Kang - One of the best experts on this subject based on the ideXlab platform.
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Motion-compensated hand-held common-path Fourier-domain optical coherence tomography probe for Image-Guided Intervention
Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XVII, 2013Co-Authors: Yong Huang, Cheol Song, Xuan Liu, Jin U KangAbstract:A motion-compensated hand-held common-path Fourier-domain optical coherence tomography imaging probe has been developed for image guided Intervention during microsurgery. A hand-held prototype instrument was designed and fabricated by integrating an imaging fiber probe inside a stainless steel needle which is attached to the ceramic shaft of a piezoelectric motor housed in an aluminum handle. The fiber probe obtains A-scan images. The distance information was extracted from the A-scans to track the sample surface distance and a fixed distance was maintained by a feedback motor control which effectively compensated hand tremor and target movements in the axial direction. Graphical user interface, real-time data processing, and visualization based on a CPU-GPU hybrid programming architecture were developed and used in the implantation of this system. To validate the system, free-hand optical coherence tomography images using various samples were obtained. The system can be easily integrated into microsurgical tools and robotics for a wide range of clinical applications. Such tools could offer physicians the freedom to easily image sites of interest with reduced risk and higher image quality.
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Motion-compensated hand-held common-path Fourier-domain optical coherence tomography probe for Image-Guided Intervention
Biomedical Optics Express, 2012Co-Authors: Yong Huang, Cheol Song, Xuan Liu, Jin U KangAbstract:A motion-compensated, hand-held, common-path, Fourier- domain optical coherence tomography imaging probe has been developed for Image-Guided Intervention during microsurgery. A hand-held prototype instrument was achieved by integrating an imaging fiber probe inside a stainless steel needle and attached to the ceramic shaft of a piezoelectric motor housed in an aluminum handle. The fiber probe obtains A-scan images. The distance information was extracted from the A-scans to track the sample surface distance and a fixed distance was maintained by a feedback motor control which effectively compensated hand tremor and target movements in the axial direction. Real-time data acquisition, processing, motion compensation, and image visualization and saving were implemented on a custom CPU-GPU hybrid architecture. We performed 10× zero padding to the raw spectrum to obtain 0.16 µm position accuracy with a compensation rate of 460 Hz. The root-mean-square error of hand- held distance variation from target position was measured to be 2.93 µm. We used a cross-correlation maximization-based shift correction algorithm for topology correction. To validate the system, we performed free-hand OCT M-scan imaging using various samples.
Stephen T. C. Wong - One of the best experts on this subject based on the ideXlab platform.
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MIAR - A motion correction algorithm for microendoscope video computing in Image-Guided Intervention
Lecture Notes in Computer Science, 2010Co-Authors: Zhong Xue, Weixin Xie, Solomon Wong, Kelvin K. Wong, Miguel Valdivia Y Alvarado, Stephen T. C. WongAbstract:In multimodality Image-Guided Intervention for cancer diagnosis, a needle with cannula is first punctured using CT or MRI -guided system to target the tumor, then microendoscopy can be performed using an optical fiber through the same cannula. With real-time optical imaging, the operator can directly determine the malignance of the tumor or perform fine needle aspiration biopsy for further diagnosis. During this operation, stable microendoscopy image series are needed to quantify the tissue properties, but they are often affected by respiratory and heart systole motion even when the Interventional probe is held steadily. This paper proposes a microendoscopy motion correction (MMC) algorithm using normalized mutual information (NMI)-based registration and a nonlinear system to model the longitudinal global transformations. Cubature Kalman filter is thus used to solve the underlying longitudinal transformations, which yields more stable and robust motion estimation. After global motion correction, longitudinal deformations among the image sequences are calculated to further refine the local tissue motion. Experimental results showed that compared to global and deformable image registrations, MMC yields more accurate alignment results for both simulated and real data.
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MIAR - Peripheral lung cancer detection by vascular tumor labeling using in-vivo microendoscopy under real time 3D CT image guided Intervention
Lecture Notes in Computer Science, 2010Co-Authors: Miguel Valdivia Y Alvarado, Zhong Xue, Stephen T. C. Wong, Kelvin K. WongAbstract:We designed and evaluated a real time 3D CT Image Guided Intervention system that integrates in-vivo microendoscopic imaging for on-the-spot visualization of ICG contrast uptake by tumor vessel in peripheral lung tumors. The performance of the system was evaluated in seven rabbits where VX2 cells were implanted in the chest to create peripheral lung tumors. Two weeks later the animal underwent a chest CT scan which was used for creating a real time 3D vision and navigation tracking. ICG was injected fifteen minutes prior to the needle puncture to allow adequate contrast leakage inside the tumor and plasma clearance. After the needle puncture, the microendoscope was introduced inside the tumor for imaging. Visualization of tumor leaky vasculature was possible in all the tumors. The experiment demonstrated that real-time microendoscopy of deep solid organs under a 3D CT Image-Guided system is possible while providing enough accuracy in reaching tumors without complications.
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ISBI - VOLES: Vascularity-Oriented LEvel Set algorithm for pulmonary vessel segmentation in image guided Intervention therapy
2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2009Co-Authors: Xiangjun Zhu, Xin Gao, Zhong Xue, Yisheng Zhu, Stephen T. C. WongAbstract:Delicate surgical planning and accurate guidance plays an important role in successful image guided Intervention. In Interventional lung cancer diagnosis and treatments, precise segmentation of pulmonary vessels from lung CT images provides vital visualization for pre-op planning and inra-op guidance to avoid major vessel damage. While simple thresholding and window/level setting can briefly segment different tissues, their results are not accurate. Recently, level set methods have been increasingly and successfully used in various organ segmentations, however, the penalty on large curvature makes the evolution along vascular structure slow, thus rendering difficulty in lung vessels. In this paper, we propose a Vascularity-Oriented LEvel Set algorithm (VOLES) to offset the curvature effect on the evolving front along vessel directions, also the evolution direction can be adaptively adjusted based on the joint intensity and vesselness statistics to prevent leakage and to adapt to intensity inhomogeneity. The VOLES algorithm is validated using lung CT images in the experiments, and results show it outperforms the traditional level set method on pulmonary vessel segmentation.
Yong Huang - One of the best experts on this subject based on the ideXlab platform.
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Motion-compensated hand-held common-path Fourier-domain optical coherence tomography probe for Image-Guided Intervention
Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XVII, 2013Co-Authors: Yong Huang, Cheol Song, Xuan Liu, Jin U KangAbstract:A motion-compensated hand-held common-path Fourier-domain optical coherence tomography imaging probe has been developed for image guided Intervention during microsurgery. A hand-held prototype instrument was designed and fabricated by integrating an imaging fiber probe inside a stainless steel needle which is attached to the ceramic shaft of a piezoelectric motor housed in an aluminum handle. The fiber probe obtains A-scan images. The distance information was extracted from the A-scans to track the sample surface distance and a fixed distance was maintained by a feedback motor control which effectively compensated hand tremor and target movements in the axial direction. Graphical user interface, real-time data processing, and visualization based on a CPU-GPU hybrid programming architecture were developed and used in the implantation of this system. To validate the system, free-hand optical coherence tomography images using various samples were obtained. The system can be easily integrated into microsurgical tools and robotics for a wide range of clinical applications. Such tools could offer physicians the freedom to easily image sites of interest with reduced risk and higher image quality.
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Motion-compensated hand-held common-path Fourier-domain optical coherence tomography probe for Image-Guided Intervention
Biomedical Optics Express, 2012Co-Authors: Yong Huang, Cheol Song, Xuan Liu, Jin U KangAbstract:A motion-compensated, hand-held, common-path, Fourier- domain optical coherence tomography imaging probe has been developed for Image-Guided Intervention during microsurgery. A hand-held prototype instrument was achieved by integrating an imaging fiber probe inside a stainless steel needle and attached to the ceramic shaft of a piezoelectric motor housed in an aluminum handle. The fiber probe obtains A-scan images. The distance information was extracted from the A-scans to track the sample surface distance and a fixed distance was maintained by a feedback motor control which effectively compensated hand tremor and target movements in the axial direction. Real-time data acquisition, processing, motion compensation, and image visualization and saving were implemented on a custom CPU-GPU hybrid architecture. We performed 10× zero padding to the raw spectrum to obtain 0.16 µm position accuracy with a compensation rate of 460 Hz. The root-mean-square error of hand- held distance variation from target position was measured to be 2.93 µm. We used a cross-correlation maximization-based shift correction algorithm for topology correction. To validate the system, we performed free-hand OCT M-scan imaging using various samples.
Zhong Xue - One of the best experts on this subject based on the ideXlab platform.
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MIAR - A motion correction algorithm for microendoscope video computing in Image-Guided Intervention
Lecture Notes in Computer Science, 2010Co-Authors: Zhong Xue, Weixin Xie, Solomon Wong, Kelvin K. Wong, Miguel Valdivia Y Alvarado, Stephen T. C. WongAbstract:In multimodality Image-Guided Intervention for cancer diagnosis, a needle with cannula is first punctured using CT or MRI -guided system to target the tumor, then microendoscopy can be performed using an optical fiber through the same cannula. With real-time optical imaging, the operator can directly determine the malignance of the tumor or perform fine needle aspiration biopsy for further diagnosis. During this operation, stable microendoscopy image series are needed to quantify the tissue properties, but they are often affected by respiratory and heart systole motion even when the Interventional probe is held steadily. This paper proposes a microendoscopy motion correction (MMC) algorithm using normalized mutual information (NMI)-based registration and a nonlinear system to model the longitudinal global transformations. Cubature Kalman filter is thus used to solve the underlying longitudinal transformations, which yields more stable and robust motion estimation. After global motion correction, longitudinal deformations among the image sequences are calculated to further refine the local tissue motion. Experimental results showed that compared to global and deformable image registrations, MMC yields more accurate alignment results for both simulated and real data.
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MIAR - Peripheral lung cancer detection by vascular tumor labeling using in-vivo microendoscopy under real time 3D CT image guided Intervention
Lecture Notes in Computer Science, 2010Co-Authors: Miguel Valdivia Y Alvarado, Zhong Xue, Stephen T. C. Wong, Kelvin K. WongAbstract:We designed and evaluated a real time 3D CT Image Guided Intervention system that integrates in-vivo microendoscopic imaging for on-the-spot visualization of ICG contrast uptake by tumor vessel in peripheral lung tumors. The performance of the system was evaluated in seven rabbits where VX2 cells were implanted in the chest to create peripheral lung tumors. Two weeks later the animal underwent a chest CT scan which was used for creating a real time 3D vision and navigation tracking. ICG was injected fifteen minutes prior to the needle puncture to allow adequate contrast leakage inside the tumor and plasma clearance. After the needle puncture, the microendoscope was introduced inside the tumor for imaging. Visualization of tumor leaky vasculature was possible in all the tumors. The experiment demonstrated that real-time microendoscopy of deep solid organs under a 3D CT Image-Guided system is possible while providing enough accuracy in reaching tumors without complications.
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ISBI - VOLES: Vascularity-Oriented LEvel Set algorithm for pulmonary vessel segmentation in image guided Intervention therapy
2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2009Co-Authors: Xiangjun Zhu, Xin Gao, Zhong Xue, Yisheng Zhu, Stephen T. C. WongAbstract:Delicate surgical planning and accurate guidance plays an important role in successful image guided Intervention. In Interventional lung cancer diagnosis and treatments, precise segmentation of pulmonary vessels from lung CT images provides vital visualization for pre-op planning and inra-op guidance to avoid major vessel damage. While simple thresholding and window/level setting can briefly segment different tissues, their results are not accurate. Recently, level set methods have been increasingly and successfully used in various organ segmentations, however, the penalty on large curvature makes the evolution along vascular structure slow, thus rendering difficulty in lung vessels. In this paper, we propose a Vascularity-Oriented LEvel Set algorithm (VOLES) to offset the curvature effect on the evolving front along vessel directions, also the evolution direction can be adaptively adjusted based on the joint intensity and vesselness statistics to prevent leakage and to adapt to intensity inhomogeneity. The VOLES algorithm is validated using lung CT images in the experiments, and results show it outperforms the traditional level set method on pulmonary vessel segmentation.
Kelvin K. Wong - One of the best experts on this subject based on the ideXlab platform.
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MIAR - A motion correction algorithm for microendoscope video computing in Image-Guided Intervention
Lecture Notes in Computer Science, 2010Co-Authors: Zhong Xue, Weixin Xie, Solomon Wong, Kelvin K. Wong, Miguel Valdivia Y Alvarado, Stephen T. C. WongAbstract:In multimodality Image-Guided Intervention for cancer diagnosis, a needle with cannula is first punctured using CT or MRI -guided system to target the tumor, then microendoscopy can be performed using an optical fiber through the same cannula. With real-time optical imaging, the operator can directly determine the malignance of the tumor or perform fine needle aspiration biopsy for further diagnosis. During this operation, stable microendoscopy image series are needed to quantify the tissue properties, but they are often affected by respiratory and heart systole motion even when the Interventional probe is held steadily. This paper proposes a microendoscopy motion correction (MMC) algorithm using normalized mutual information (NMI)-based registration and a nonlinear system to model the longitudinal global transformations. Cubature Kalman filter is thus used to solve the underlying longitudinal transformations, which yields more stable and robust motion estimation. After global motion correction, longitudinal deformations among the image sequences are calculated to further refine the local tissue motion. Experimental results showed that compared to global and deformable image registrations, MMC yields more accurate alignment results for both simulated and real data.
-
MIAR - Peripheral lung cancer detection by vascular tumor labeling using in-vivo microendoscopy under real time 3D CT image guided Intervention
Lecture Notes in Computer Science, 2010Co-Authors: Miguel Valdivia Y Alvarado, Zhong Xue, Stephen T. C. Wong, Kelvin K. WongAbstract:We designed and evaluated a real time 3D CT Image Guided Intervention system that integrates in-vivo microendoscopic imaging for on-the-spot visualization of ICG contrast uptake by tumor vessel in peripheral lung tumors. The performance of the system was evaluated in seven rabbits where VX2 cells were implanted in the chest to create peripheral lung tumors. Two weeks later the animal underwent a chest CT scan which was used for creating a real time 3D vision and navigation tracking. ICG was injected fifteen minutes prior to the needle puncture to allow adequate contrast leakage inside the tumor and plasma clearance. After the needle puncture, the microendoscope was introduced inside the tumor for imaging. Visualization of tumor leaky vasculature was possible in all the tumors. The experiment demonstrated that real-time microendoscopy of deep solid organs under a 3D CT Image-Guided system is possible while providing enough accuracy in reaching tumors without complications.