Dr. Shijun Wang Profile

Dr. Shijun Wang

Visiting Fellow (Postdoc) at National Institutes of Health

SPIE Involvement:

Author

Publications (18)

Proceedings Article | 21 March 2016 Paper

Paper

Active appearance model and deep learning for more accurate prostate segmentation on MRI

Ruida Cheng, Holger Roth, Le Lu, Shijun Wang, Baris Turkbey, William Gandler, Evan McCreedy, Harsh Agarwal, Peter Choyke, Ronald Summers, Matthew McAuliffe

Proceedings Volume 9784, 97842I (2016) https://doi.org/10.1117/12.2216286

KEYWORDS: Image segmentation, 3D modeling, Prostate, Magnetic resonance imaging, Machine learning, 3D image processing, Pattern recognition, Image analysis, Data modeling, Principal component analysis, Statistical modeling, Cancer

Read Abstract +

Proceedings Article | 20 March 2015 Paper

Paper

Efficient Hilbert transform-based alternative to Tofts physiological models for representing MRI dynamic contrast-enhanced images in computer-aided diagnosis of prostate cancer

Kevin Boehm, Shijun Wang, Karen Burtt, Baris Turkbey, Samuel Weisenthal, Peter Pinto, Peter Choyke, Bradford Wood, Nicholas Petrick, Berkman Sahiner, Ronald Summers

Proceedings Volume 9414, 94140S (2015) https://doi.org/10.1117/12.2082309

KEYWORDS: Computer aided diagnosis and therapy, Magnetic resonance imaging, Prostate cancer, Tissues, Data modeling, Systems modeling, Cancer, Solid modeling, Tumor growth modeling, Feature extraction

Read Abstract +

Proceedings Article | 21 March 2014 Paper

Paper

Locally constrained active contour: a region-based level set for ovarian cancer metastasis segmentation

Jianfei Liu, Jianhua Yao, Shijun Wang, Marius George Linguraru, Ronald Summers

Proceedings Volume 9034, 903404 (2014) https://doi.org/10.1117/12.2043712

KEYWORDS: Image segmentation, Tumors, Ovarian cancer, Image processing algorithms and systems, Computed tomography, Adaptive optics, Liver, Spleen, Image analysis, Evolutionary algorithms

Read Abstract +

Proceedings Article | 18 March 2014 Paper

Paper

Abdominal lymphadenopathy detection using random forest

Kevin Cherry, Shijun Wang, Evrim Turkbey, Ronald Summers

Proceedings Volume 9035, 90351G (2014) https://doi.org/10.1117/12.2043837

KEYWORDS: Lymphatic system, Computed tomography, Feature extraction, CAD systems, Computer aided diagnosis and therapy, Computing systems, Image segmentation, Feature selection, Abdomen

Read Abstract +

Proceedings Article | 18 March 2014 Paper

Paper

Mediastinal lymph node detection on thoracic CT scans using spatial prior from multi-atlas label fusion

Jiamin Liu, Jocelyn Zhao, Joanne Hoffman, Jianhua Yao, Weidong Zhang, Evrim Turkbey, Shijun Wang, Christine Kim, Ronald Summers

Proceedings Volume 9035, 90350M (2014) https://doi.org/10.1117/12.2043737

KEYWORDS: Lymphatic system, Image segmentation, Computed tomography, Lung, Esophagus, Heart, Chest, 3D image processing, Feature extraction, Spine

Read Abstract +

Proceedings Article | 18 March 2013 Paper

Paper

Robust detection of renal calculi from non-contract CT images using TV-flow and MSER features

Jianfei Liu, Shijun Wang, Marius George Linguraru, Ronald Summers

Proceedings Volume 8670, 867006 (2013) https://doi.org/10.1117/12.2008034

KEYWORDS: Renal calculi, Image segmentation, Kidney, Calculi, Calculus, Detection and tracking algorithms, Image processing, Computed tomography, Diffusion, Computer aided diagnosis and therapy

Read Abstract +

Proceedings Article | 18 March 2013 Paper

Paper

Automatic segmentation of kidneys from non-contrast CT images using efficient belief propagation

Jianfei Liu, Marius George Linguraru, Shijun Wang, Ronald Summers

Proceedings Volume 8670, 867005 (2013) https://doi.org/10.1117/12.2007738

KEYWORDS: Kidney, Image segmentation, Liver, Spleen, Computed tomography, Image registration, Image processing, Virtual colonoscopy, Abdomen, Computer aided diagnosis and therapy

Read Abstract +

Proceedings Article | 26 February 2013 Paper

Paper

A prostate cancer computer-aided diagnosis system using multimodal magnetic resonance imaging and targeted biopsy labels

Peter Liu, Shijun Wang, Baris Turkbey, Kinzya Grant, Peter Pinto, Peter Choyke, Bradford Wood, Ronald Summers

Proceedings Volume 8670, 86701G (2013) https://doi.org/10.1117/12.2007927

KEYWORDS: Magnetic resonance imaging, Biopsy, Prostate cancer, Imaging systems, Diffusion weighted imaging, Prostate, Computer aided diagnosis and therapy, Cancer, Feature extraction, Computing systems

Read Abstract +

Proceedings Article | 14 April 2012 Paper

Paper

Robust automated detection, segmentation, and classification of hepatic tumors from CT data

Marius George Linguraru, William Richbourg, Vivek Pamulapati, Shijun Wang, Ronald Summers

Proceedings Volume 8317, 83170J (2012) https://doi.org/10.1117/12.910617

KEYWORDS: Tumors, Image segmentation, Liver, Feature extraction, Liver cancer, Feature selection, Computed tomography, Cancer, Error analysis, Binary data

Read Abstract +

Proceedings Article | 23 February 2012 Paper

Paper

Computer-aided marginal artery detection on computed tomographic colonography

Zhuoshi Wei, Jianhua Yao, Shijun Wang, Jiamin Liu, Ronald Summers

Proceedings Volume 8315, 83150Z (2012) https://doi.org/10.1117/12.911850

KEYWORDS: Arteries, Colon, Computer aided diagnosis and therapy, Tomography, Image segmentation, Blood vessels, Blood, Computer aided design, Shape memory alloys

Read Abstract +

Proceedings Article | 23 February 2012 Paper

Paper

Computer vision approach to detect colonic polyps in computed tomographic colonography

Matthew McKenna, Shijun Wang, Tan Nguyen, Joseph Burns, Nicholas Petrick, Berkman Sahiner, Ronald Summers

Proceedings Volume 8315, 83151S (2012) https://doi.org/10.1117/12.911657

KEYWORDS: Video, Computer aided diagnosis and therapy, Tomography, Machine vision, Computer vision technology, Algorithm development, Image classification, Diagnostics, Computed tomography, Cameras

Read Abstract +

Proceedings Article | 9 March 2011 Paper

Paper

Computer-aided teniae coli detection using height maps from computed tomographic colonography images

Zhuoshi Wei, Jianhua Yao, Shijun Wang, Ronald Summers

Proceedings Volume 7963, 79631G (2011) https://doi.org/10.1117/12.878257

KEYWORDS: Colon, Image filtering, Virtual colonoscopy, Computer aided diagnosis and therapy, Tomography, 3D image processing, Image segmentation, Cancer, Feature extraction, Detection and tracking algorithms

Read Abstract +

Proceedings Article | 9 March 2011 Paper

Paper

3D supine and prone colon registration for computed tomographic colonography scans based on graph matching

Shijun Wang, Nicholas Petrick, Robert Van Uitert, Senthil Periaswamy, Ronald Summers

Proceedings Volume 7963, 79631F (2011) https://doi.org/10.1117/12.878227

KEYWORDS: Colon, Error analysis, Tomography, Virtual colonoscopy, Reconstruction algorithms, 3D image processing, Computer aided diagnosis and therapy, Algorithms, Colorectal cancer, Medical imaging

Read Abstract +

Proceedings Article | 9 March 2010 Paper

Paper

Matching colonic polyps using correlation optimized warping

Shijun Wang, Jianhua Yao, Nicholas Petrick, Ronald Summers

Proceedings Volume 7624, 76240E (2010) https://doi.org/10.1117/12.844352

KEYWORDS: Colon, Computer aided diagnosis and therapy, Computer aided design, Tomography, Colorectal cancer, Virtual colonoscopy, Computing systems, Machine learning, Computed tomography, Radiology

Read Abstract +

Proceedings Article | 3 March 2009 Paper

Paper

High-performance computer aided detection system for polyp detection in CT colonography with fluid and fecal tagging

Jiamin Liu, Shijun Wang, Suraj Kabadi, Ronald Summers

Proceedings Volume 7260, 72601B (2009) https://doi.org/10.1117/12.811654

KEYWORDS: CAD systems, Virtual colonoscopy, Computer aided diagnosis and therapy, Image segmentation, Signal attenuation, Computed tomography, Colon, Diffusion, Tissues, Colorectal cancer

Read Abstract +

CT colonography (CTC) is a feasible and minimally invasive method for the detection of colorectal polyps and cancer screening. Computer-aided detection (CAD) of polyps has improved consistency and sensitivity of virtual colonoscopy interpretation and reduced interpretation burden. A CAD system typically consists of four stages: (1) image preprocessing including colon segmentation; (2) initial detection generation; (3) feature selection; and (4) detection classification. In our experience, three existing problems limit the performance of our current CAD system. First, highdensity orally administered contrast agents in fecal-tagging CTC have scatter effects on neighboring tissues. The scattering manifests itself as an artificial elevation in the observed CT attenuation values of the neighboring tissues. This pseudo-enhancement phenomenon presents a problem for the application of computer-aided polyp detection, especially when polyps are submerged in the contrast agents. Second, general kernel approach for surface curvature computation in the second stage of our CAD system could yield erroneous results for thin structures such as small (6-9 mm) polyps and for touching structures such as polyps that lie on haustral folds. Those erroneous curvatures will reduce the sensitivity of polyp detection. The third problem is that more than 150 features are selected from each polyp candidate in the third stage of our CAD system. These high dimensional features make it difficult to learn a good decision boundary for detection classification and reduce the accuracy of predictions. Therefore, an improved CAD system for polyp detection in CTC data is proposed by introducing three new techniques. First, a scale-based scatter correction algorithm is applied to reduce pseudo-enhancement effects in the image pre-processing stage. Second, a cubic spline interpolation method is utilized to accurately estimate curvatures for initial detection generation. Third, a new dimensionality reduction classifier, diffusion map and local linear embedding (DMLLE), is developed for classification and false positives (FP) reduction. Performance of the improved CAD system is evaluated and compared with our existing CAD system (without applying those techniques) using CT scans of 1186 patients. These scans are divided into a training set and a test set. The sensitivity of the improved CAD system increased 18% on training data at a rate of 5 FPs per patient and 15% on test data at a rate of 5 FPs per patient. Our results indicated that the improved CAD system achieved significantly better performance on medium-sized colonic adenomas with higher sensitivity and lower FP rate in CTC.

Proceedings Article | 28 February 2009 Paper

Paper

Combining heterogeneous features for colonic polyp detection in CTC based on semi-definite programming

Shijun Wang, Jianhua Yao, Nicholas Petrick, Ronald Summers

Proceedings Volume 7260, 72602R (2009) https://doi.org/10.1117/12.811219

KEYWORDS: Computer programming, Feature extraction, Computer aided diagnosis and therapy, Colon, Image segmentation, Colorectal cancer, Tomography, Shape analysis, CAD systems, Computer aided design

Read Abstract +

Proceedings Article | 17 March 2008 Paper

Paper

Automated matching of supine and prone colonic polyps based on PCA and SVMs

Shijun Wang, Robert Van Uitert, Ronald Summers

Proceedings Volume 6915, 69150B (2008) https://doi.org/10.1117/12.769583

KEYWORDS: Colon, Principal component analysis, Computer aided diagnosis and therapy, Feature extraction, Image segmentation, Computed tomography, Tomography, Cancer, Colorectal cancer, Computing systems

Read Abstract +

Proceedings Article | 17 March 2008 Paper

Paper

DMLLE: a large-scale dimensionality reduction method for detection of polyps in CT colonography

Shijun Wang, Jianhua Yao, Ronald Summers

Proceedings Volume 6915, 69150C (2008) https://doi.org/10.1117/12.769844

KEYWORDS: Diffusion, Computed tomography, Virtual colonoscopy, Feature extraction, Computer aided diagnosis and therapy, 3D image processing, Image segmentation, CAD systems, Dimension reduction, Computing systems

Read Abstract +

Showing 5 of 18 publications

SIGN IN TO:

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Advertisement

Advertisement