Fuxing Yang - Independent Researcher (original) (raw)
Papers by Fuxing Yang
System and Method to Measure Cardiac Ejection Fraction
System and method for bladder detection using ultrasonic harmonic imaging
System and Method for Bladder Detection Using Harmonic Imaging
System and Method for Ultrasound Harmonic Imaging
Systems and methods to improve clarity in ultrasound images
System and Method to Identify and Measure Organ Wall Boundaries
System and method for cardiac imaging
The international journal of cardiovascular imaging, 2003
Atherosclerosis leads to heart attack and stroke, which are major killers in the western world. T... more Atherosclerosis leads to heart attack and stroke, which are major killers in the western world. These cardiovascular events frequently result from local rupture of vulnerable atherosclerotic plaque. Noninvasive assessment of plaque vulnerability would dramatically change the way in which atherosclerotic disease is diagnosed, monitored, and treated. In this paper, we report a computerized method for segmentation of arterial wall layers and plaque from high-resolution volumetric MR images. The method uses dynamic programming to detect optimal borders in each MRI frame. The accuracy of the results was tested in 62 T1-weighted MR images from six vessel specimens in comparison to borders manually determined by an expert observer. The mean signed border positioning errors for the lumen, internal elastic lamina, and external elastic lamina borders were)0.1 ± 0.1, 0.0 ± 0.1, and)0.1 ± 0.1 mm, respectively. The presented wall layer segmentation approach is one of the first steps towards non-invasive assessment of plaque vulnerability in atherosclerotic subjects.
Medical Imaging 2004: Image Processing, 2004
The specific goal of our research is to develop automated methods for quantitative analysis of tu... more The specific goal of our research is to develop automated methods for quantitative analysis of tumor cells from microscopic images. By segmenting living tumor cells, cell behavior under stress can be studied. Therefore, accurate acquisition and analysis of microscope images from living cell cultures are of utmost importance. If cell behavior can be studied through their life span, cell motility and shape changes can be quantified and analyzed in relation with the severity of induced stress. Consequently, cell responses to the environment can be quantitatively analyzed. The Large Scale Digital Cell Analysis System developed at the University of Iowa provides a capability for real-time cell image acquisition. In the work presented here, feasibility of fully automated living tumor cell segmentation is demonstrated allowing future quantitative cell studies. An automated method for identification of the cell boundaries in microscopy images is presented.
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 2005
The Large Scale Digital Cell Analysis System (LSDCAS) developed at the University of Iowa provide... more The Large Scale Digital Cell Analysis System (LSDCAS) developed at the University of Iowa provides capabilities for extended-time live cell image acquisition. This paper presents a new approach to quantitative analysis of live cell image data. By using time as an extra dimension, level set methods are employed to determine cell trajectories from 2D + time data sets. When identifying the cell trajectories, cell cluster separation and mitotic cell detection steps are performed. Each of the trajectories corresponds to the motion pattern of an individual cell in the data set. At each time frame, number of cells, cell locations, cell borders, cell areas, and cell states are determined and recorded. The proposed method can help solving cell analysis problems of general importance including cell pedigree analysis and cell tracking. The developed method was tested on cancer cell image sequences and its performance compared with manually-defined ground truth. The similarity Kappa Index is 0....
Volumetric Segmentation Using Shape Models In The Level Set Framework
Deformable Models, 2007
... In addition, the reader will be shown how statistical shape in-formation can be extracted fro... more ... In addition, the reader will be shown how statistical shape in-formation can be extracted from a training procedure and combined with regional information for segmentation. ... (a) (b) (c) Figure 5. Pulmonary airway tree segmentation using 3D Fast Marching Methods: (a) result ...
Medical Imaging 2003: Image Processing, 2003
ABSTRACT Cardiovascular events frequently result from local rupture of vulnerable atherosclerotic... more ABSTRACT Cardiovascular events frequently result from local rupture of vulnerable atherosclerotic plaque. Non-invasive assessment of plaque vulnerability is needed to allow institution of preventive measures before heart attack or stroke occur. A computerized method for segmentation of arterial wall layers and plaque from high-resolution volumetric MR images is reported. The method uses dynamic programming to detect optimal borders in each MRI frame. The accuracy of the results was tested in 62 T1-weighted MR images from 6 vessel specimens in comparison to borders manually determined by an expert observer. The mean signed border positioning errors for the lumen, internal elastic lamina, and external elastic lamina borders were -0.12+/-0.14 mm, 0.04+/-0.12mm, and -0.15+/-0.13 mm, respectively. The presented wall layer segmentation approach is one of the first steps towards non-invasive assessment of plaque vulnerability in atherosclerotic subjects.
Medical Imaging 2004: Visualization, Image-Guided Procedures, and Display, 2004
This work describes a method for detecting mitotic cells in time-lapse microscopy images of live ... more This work describes a method for detecting mitotic cells in time-lapse microscopy images of live cells. The image sequences are from the Large Scale Digital Cell Analysis System (LSDCAS) at the University of Iowa. LSDCAS is an automated microscope system capable of monitoring 1000 microscope fields over time intervals of up to one month. Manual analysis of the image sequences can be extremely time consuming. This work is part of a larger project to automate the image sequence analysis. A three-step approach is used. In the first step, potential mitotic cells are located in the image sequences. In the second step, object border segmentation is performed with the watershed algorithm. Objects in adjacent frames are grouped into object sequences for classification. In the third step, the image sequences are converted to feature vector sequences. The feature vectors contain spatial and temporal information. Hidden Markov Models (HMMs) are used to classify the feature vector sequences into dead cells, cell edges, and dividing cells. Discrete and continuous HMMs were trained on 500 sequences. The discrete HMM recognition rates were 62% for dead cells, 77% for cell edges, and 75% for dividing cells. The continuous HMM results were 68%, 88% and 77%.
3D ultrasound-based instrument for non-invasive measurement of amniotic fluid volume
The Journal of the Acoustical Society of America, 2007
System and method for cardiac imaging
The Journal of the Acoustical Society of America, 2009
International Congress Series, 2005
Synectin/syndecan-4 regulate coronary arteriolar growth during development
Developmental Dynamics, 2007
Syndecan-4 and its cytoplasmic binding partner, synectin, are known to play a role in FGF-2 signa... more Syndecan-4 and its cytoplasmic binding partner, synectin, are known to play a role in FGF-2 signaling and vascular growth. To determine their roles in coronary artery/arteriolar formation and growth, we compared syndecan-4 and synectin null mice with their wild-type counterparts. Image analysis of arterioles visualized by smooth muscle alpha-actin immunostaining revealed that synectin (-/-) mice had lower arteriolar length and volume densities than wild-type mice. As shown by electron microscopic analysis, arterioles from the two did not differ in morphology, including their endothelial cell junctions, and the organization and distribution of smooth muscle. Using micro-computer tomography, we found that the size and branching patterns of coronary arteries (diameters > 50 microm) were similar for the two groups, a finding that indicates that the growth of arteries is not influenced by a loss of synectin. Syndecan-4 null male mice also had lower arteriolar length densities than their gender wild-type controls. However, female syndecan-4 null mice were characterized by higher arteriolar length and volume densities than their gender-matched wild-type controls. Thus, we conclude that both synectin and syndecan-4 play a role in arteriolar development, a finding that is consistent with previous evidence that FGF-2 plays a role in coronary arterial growth. Moreover, our data reveal that gender influences the arteriolar growth response to syndecan-4 but not to synectin.
Atherosclerosis leads to heart attack and stroke, which are major killers in the western world. T... more Atherosclerosis leads to heart attack and stroke, which are major killers in the western world. These cardiovascular events frequently result from local rupture of vulnerable atherosclerotic plaque. Noninvasive assessment of plaque vulnerability would dramatically change the way in which atherosclerotic disease is diagnosed, monitored, and treated. In this paper, we report a computerized method for segmentation of arterial wall layers and plaque from high-resolution volumetric MR images. The method uses dynamic programming to detect optimal borders in each MRI frame. The accuracy of the results was tested in 62 T1-weighted MR images from six vessel specimens in comparison to borders manually determined by an expert observer. The mean signed border positioning errors for the lumen, internal elastic lamina, and external elastic lamina borders were)0.1 ± 0.1, 0.0 ± 0.1, and)0.1 ± 0.1 mm, respectively. The presented wall layer segmentation approach is one of the first steps towards non-invasive assessment of plaque vulnerability in atherosclerotic subjects.
Quantitative analysis of two-phase 3D+ time aortic MR images
ABSTRACT Automated and accurate segmentation of the aorta in 3D+time MR image data is important f... more ABSTRACT Automated and accurate segmentation of the aorta in 3D+time MR image data is important for early detection of connective tissue disorders leading to aortic aneurysms and dissections. A computer-aided diagnosis method is reported that allows the objective identification of subjects with connective tissue disorders from two-phase 3D+time aortic MR images. Our automated segmentation method combines level-set and optimal border detection. The resulting aortic lumen surface was registered with an aortic model followed by calculation of modal indices of aortic shape and motion. The modal indices reflect the differences of any individual aortic shape and motion from an average aortic behavior. The indices were input to a Support Vector Machine (SVM) classifier and a discrimination model was constructed. 3D+time MR image data sets acquired from 22 normal and connective tissue disorder subjects at end-diastole (R-wave peak) and at 45% of the R-R interval were used to evaluate the performance of our method. The automated D segmentation result produced accurate aortic surfaces covering the aorta from the left-ventricular outflow tract to the diaphragm and yielded subvoxel accuracy with signed surface positioning errors of -0.09+/-1.21 voxel (-0.15+/-2.11 mm). The computer aided diagnosis method distinguished between normal and connective tissue disorder subjects with a classification correctness of 90.1 %.
System and Method to Measure Cardiac Ejection Fraction
System and method for bladder detection using ultrasonic harmonic imaging
System and Method for Bladder Detection Using Harmonic Imaging
System and Method for Ultrasound Harmonic Imaging
Systems and methods to improve clarity in ultrasound images
System and Method to Identify and Measure Organ Wall Boundaries
System and method for cardiac imaging
The international journal of cardiovascular imaging, 2003
Atherosclerosis leads to heart attack and stroke, which are major killers in the western world. T... more Atherosclerosis leads to heart attack and stroke, which are major killers in the western world. These cardiovascular events frequently result from local rupture of vulnerable atherosclerotic plaque. Noninvasive assessment of plaque vulnerability would dramatically change the way in which atherosclerotic disease is diagnosed, monitored, and treated. In this paper, we report a computerized method for segmentation of arterial wall layers and plaque from high-resolution volumetric MR images. The method uses dynamic programming to detect optimal borders in each MRI frame. The accuracy of the results was tested in 62 T1-weighted MR images from six vessel specimens in comparison to borders manually determined by an expert observer. The mean signed border positioning errors for the lumen, internal elastic lamina, and external elastic lamina borders were)0.1 ± 0.1, 0.0 ± 0.1, and)0.1 ± 0.1 mm, respectively. The presented wall layer segmentation approach is one of the first steps towards non-invasive assessment of plaque vulnerability in atherosclerotic subjects.
Medical Imaging 2004: Image Processing, 2004
The specific goal of our research is to develop automated methods for quantitative analysis of tu... more The specific goal of our research is to develop automated methods for quantitative analysis of tumor cells from microscopic images. By segmenting living tumor cells, cell behavior under stress can be studied. Therefore, accurate acquisition and analysis of microscope images from living cell cultures are of utmost importance. If cell behavior can be studied through their life span, cell motility and shape changes can be quantified and analyzed in relation with the severity of induced stress. Consequently, cell responses to the environment can be quantitatively analyzed. The Large Scale Digital Cell Analysis System developed at the University of Iowa provides a capability for real-time cell image acquisition. In the work presented here, feasibility of fully automated living tumor cell segmentation is demonstrated allowing future quantitative cell studies. An automated method for identification of the cell boundaries in microscopy images is presented.
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 2005
The Large Scale Digital Cell Analysis System (LSDCAS) developed at the University of Iowa provide... more The Large Scale Digital Cell Analysis System (LSDCAS) developed at the University of Iowa provides capabilities for extended-time live cell image acquisition. This paper presents a new approach to quantitative analysis of live cell image data. By using time as an extra dimension, level set methods are employed to determine cell trajectories from 2D + time data sets. When identifying the cell trajectories, cell cluster separation and mitotic cell detection steps are performed. Each of the trajectories corresponds to the motion pattern of an individual cell in the data set. At each time frame, number of cells, cell locations, cell borders, cell areas, and cell states are determined and recorded. The proposed method can help solving cell analysis problems of general importance including cell pedigree analysis and cell tracking. The developed method was tested on cancer cell image sequences and its performance compared with manually-defined ground truth. The similarity Kappa Index is 0....
Volumetric Segmentation Using Shape Models In The Level Set Framework
Deformable Models, 2007
... In addition, the reader will be shown how statistical shape in-formation can be extracted fro... more ... In addition, the reader will be shown how statistical shape in-formation can be extracted from a training procedure and combined with regional information for segmentation. ... (a) (b) (c) Figure 5. Pulmonary airway tree segmentation using 3D Fast Marching Methods: (a) result ...
Medical Imaging 2003: Image Processing, 2003
ABSTRACT Cardiovascular events frequently result from local rupture of vulnerable atherosclerotic... more ABSTRACT Cardiovascular events frequently result from local rupture of vulnerable atherosclerotic plaque. Non-invasive assessment of plaque vulnerability is needed to allow institution of preventive measures before heart attack or stroke occur. A computerized method for segmentation of arterial wall layers and plaque from high-resolution volumetric MR images is reported. The method uses dynamic programming to detect optimal borders in each MRI frame. The accuracy of the results was tested in 62 T1-weighted MR images from 6 vessel specimens in comparison to borders manually determined by an expert observer. The mean signed border positioning errors for the lumen, internal elastic lamina, and external elastic lamina borders were -0.12+/-0.14 mm, 0.04+/-0.12mm, and -0.15+/-0.13 mm, respectively. The presented wall layer segmentation approach is one of the first steps towards non-invasive assessment of plaque vulnerability in atherosclerotic subjects.
Medical Imaging 2004: Visualization, Image-Guided Procedures, and Display, 2004
This work describes a method for detecting mitotic cells in time-lapse microscopy images of live ... more This work describes a method for detecting mitotic cells in time-lapse microscopy images of live cells. The image sequences are from the Large Scale Digital Cell Analysis System (LSDCAS) at the University of Iowa. LSDCAS is an automated microscope system capable of monitoring 1000 microscope fields over time intervals of up to one month. Manual analysis of the image sequences can be extremely time consuming. This work is part of a larger project to automate the image sequence analysis. A three-step approach is used. In the first step, potential mitotic cells are located in the image sequences. In the second step, object border segmentation is performed with the watershed algorithm. Objects in adjacent frames are grouped into object sequences for classification. In the third step, the image sequences are converted to feature vector sequences. The feature vectors contain spatial and temporal information. Hidden Markov Models (HMMs) are used to classify the feature vector sequences into dead cells, cell edges, and dividing cells. Discrete and continuous HMMs were trained on 500 sequences. The discrete HMM recognition rates were 62% for dead cells, 77% for cell edges, and 75% for dividing cells. The continuous HMM results were 68%, 88% and 77%.
3D ultrasound-based instrument for non-invasive measurement of amniotic fluid volume
The Journal of the Acoustical Society of America, 2007
System and method for cardiac imaging
The Journal of the Acoustical Society of America, 2009
International Congress Series, 2005
Synectin/syndecan-4 regulate coronary arteriolar growth during development
Developmental Dynamics, 2007
Syndecan-4 and its cytoplasmic binding partner, synectin, are known to play a role in FGF-2 signa... more Syndecan-4 and its cytoplasmic binding partner, synectin, are known to play a role in FGF-2 signaling and vascular growth. To determine their roles in coronary artery/arteriolar formation and growth, we compared syndecan-4 and synectin null mice with their wild-type counterparts. Image analysis of arterioles visualized by smooth muscle alpha-actin immunostaining revealed that synectin (-/-) mice had lower arteriolar length and volume densities than wild-type mice. As shown by electron microscopic analysis, arterioles from the two did not differ in morphology, including their endothelial cell junctions, and the organization and distribution of smooth muscle. Using micro-computer tomography, we found that the size and branching patterns of coronary arteries (diameters > 50 microm) were similar for the two groups, a finding that indicates that the growth of arteries is not influenced by a loss of synectin. Syndecan-4 null male mice also had lower arteriolar length densities than their gender wild-type controls. However, female syndecan-4 null mice were characterized by higher arteriolar length and volume densities than their gender-matched wild-type controls. Thus, we conclude that both synectin and syndecan-4 play a role in arteriolar development, a finding that is consistent with previous evidence that FGF-2 plays a role in coronary arterial growth. Moreover, our data reveal that gender influences the arteriolar growth response to syndecan-4 but not to synectin.
Atherosclerosis leads to heart attack and stroke, which are major killers in the western world. T... more Atherosclerosis leads to heart attack and stroke, which are major killers in the western world. These cardiovascular events frequently result from local rupture of vulnerable atherosclerotic plaque. Noninvasive assessment of plaque vulnerability would dramatically change the way in which atherosclerotic disease is diagnosed, monitored, and treated. In this paper, we report a computerized method for segmentation of arterial wall layers and plaque from high-resolution volumetric MR images. The method uses dynamic programming to detect optimal borders in each MRI frame. The accuracy of the results was tested in 62 T1-weighted MR images from six vessel specimens in comparison to borders manually determined by an expert observer. The mean signed border positioning errors for the lumen, internal elastic lamina, and external elastic lamina borders were)0.1 ± 0.1, 0.0 ± 0.1, and)0.1 ± 0.1 mm, respectively. The presented wall layer segmentation approach is one of the first steps towards non-invasive assessment of plaque vulnerability in atherosclerotic subjects.
Quantitative analysis of two-phase 3D+ time aortic MR images
ABSTRACT Automated and accurate segmentation of the aorta in 3D+time MR image data is important f... more ABSTRACT Automated and accurate segmentation of the aorta in 3D+time MR image data is important for early detection of connective tissue disorders leading to aortic aneurysms and dissections. A computer-aided diagnosis method is reported that allows the objective identification of subjects with connective tissue disorders from two-phase 3D+time aortic MR images. Our automated segmentation method combines level-set and optimal border detection. The resulting aortic lumen surface was registered with an aortic model followed by calculation of modal indices of aortic shape and motion. The modal indices reflect the differences of any individual aortic shape and motion from an average aortic behavior. The indices were input to a Support Vector Machine (SVM) classifier and a discrimination model was constructed. 3D+time MR image data sets acquired from 22 normal and connective tissue disorder subjects at end-diastole (R-wave peak) and at 45% of the R-R interval were used to evaluate the performance of our method. The automated D segmentation result produced accurate aortic surfaces covering the aorta from the left-ventricular outflow tract to the diaphragm and yielded subvoxel accuracy with signed surface positioning errors of -0.09+/-1.21 voxel (-0.15+/-2.11 mm). The computer aided diagnosis method distinguished between normal and connective tissue disorder subjects with a classification correctness of 90.1 %.