Haustral Fold Segmentation With Curvature-Guided Level Set Evolution

Human colon has complex structures mostly because of the haustral folds. The folds are thin flat protrusions on the colon wall, which complicate the shape analysis for computer-aided detection (CAD) of colonic polyps. Fold segmentation may help reduce the structural complexity, and the folds can serve as an anatomic reference for computed tomographic colonography (CTC). Therefore, in this study, based on a model of the haustral fold boundaries, we developed a level-set approach to automatically segment the fold surfaces. To evaluate the developed fold segmentation algorithm, we first established the ground truth of haustral fold boundaries by experts' drawing on 15 patient CTC datasets without severe under/over colon distention from two medical centers. The segmentation algorithm successfully detected 92.7% of the folds in the ground truth. In addition to the sensitivity measure, we further developed a merit of segmented-area ratio (SAR), i.e., the ratio between the area of the intersection and union of the expert-drawn folds and the area of the automatically segmented folds, to measure the segmentation accuracy. The segmentation algorithm reached an average value of SAR = 86.2%, showing a good match with the ground truth on the fold surfaces. We believe the automatically segmented fold surfaces have the potential to benefit many postprocedures in CTC, such as CAD, taenia coli extraction, supine-prone registration, etc.

[1]  Zhengrong Liang,et al.  Increasing computer-aided detection specificity by projection features for CT colonography. , 2010, Medical physics.

[2]  Ronald M. Summers,et al.  DETECTION AND SEGMENTATION OF COLONIC POLYPS ON HAUSTRAL FOLDS , 2007, 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[3]  R. Courant,et al.  On the Partial Difference Equations, of Mathematical Physics , 2015 .

[4]  Ronald M. Summers,et al.  Teniæ Coli Detection from Colon Surface: Extraction of Anatomical Markers for Virtual Colonoscopy , 2007, ISVC.

[5]  Chitra Dorai,et al.  COSMOS - A Representation Scheme for 3D Free-Form Objects , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Alex M. Andrew,et al.  Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science (2nd edition) , 2000 .

[7]  Afra Zomorodian,et al.  Colon polyp detection using smoothed shape operators: Preliminary results , 2008, Medical Image Anal..

[8]  Hiroyuki Yoshida,et al.  Region-based supine-prone correspondence for the reduction of false-positive CAD polyp candidates in CT colonography. , 2005, Academic radiology.

[9]  Hiroyuki Yoshida,et al.  Three-dimensional computer-aided diagnosis scheme for detection of colonic polyps , 2001, IEEE Transactions on Medical Imaging.

[10]  Masahiro Oda,et al.  Haustral fold registration in CT colonography and its application to registration of virtual stretched view of the colon , 2010, Medical Imaging.

[11]  Wei Zeng,et al.  Supine and Prone Colon Registration Using Quasi-Conformal Mapping , 2010, IEEE Transactions on Visualization and Computer Graphics.

[12]  Kim,et al.  Computer-aided Detection of CT Colonography , 2009 .

[13]  A. M. Youssef,et al.  Automated polyp detection at CT colonography: feasibility assessment in a human population. , 2001, Radiology.

[14]  Zhengrong Liang,et al.  An EM approach to MAP solution of segmenting tissue mixture percentages with application to CT-based virtual colonoscopy. , 2008, Medical physics.

[15]  Jianhua Yao,et al.  Registration of prone and supine CT colonography scans using correlation optimized warping and canonical correlation analysis. , 2009, Medical physics.

[16]  Feng Qiu,et al.  Conformal virtual colon flattening , 2006, SPM '06.

[17]  Roel Truyen,et al.  Does a computer-aided detection algorithm in a second read paradigm enhance the performance of experienced computed tomography colonography readers in a population of increased risk? , 2009, European Radiology.

[18]  I. Bitter,et al.  Computed tomographic virtual colonoscopy computer-aided polyp detection in a screening population. , 2005, Gastroenterology.

[19]  Stuart A. Taylor,et al.  CT colonography: computer-aided detection of morphologically flat T1 colonic carcinoma , 2008, European Radiology.

[20]  Joseph S. B. Mitchell,et al.  The Discrete Geodesic Problem , 1987, SIAM J. Comput..

[21]  J. Hornaday,et al.  Cancer Facts & Figures 2004 , 2004 .

[22]  Ronald M. Summers,et al.  Teniae Coli Extraction in Human Colon for Computed Tomographic Colonography Images , 2010, Virtual Colonoscopy and Abdominal Imaging.

[23]  I. Williams.  Diverticular disease of the colon without diverticula. , 1967, Radiology.

[24]  Ronald M. Summers,et al.  Colonic fold detection from computed tomographic colonography images using diffusion-FCM and level sets , 2010, Pattern Recognit. Lett..

[25]  Ronald M. Summers,et al.  Teniae coli guided navigation and registration for virtual colonoscopy , 2005, VIS 05. IEEE Visualization, 2005..

[26]  Nicholas Petrick,et al.  Teniae coli-based circumferential localization system for CT colonography: feasibility study. , 2007, Radiology.

[27]  Qin Lin,et al.  Automatic teniae coli detection for computed tomography colonography , 2011, Medical Imaging.

[28]  J. Saurin,et al.  [Computed tomographic virtual colonoscopy to screen for colorectal neoplasia in asymptomatic adults]. , 2004, Gastroenterologie clinique et biologique.

[29]  Lindsay I. Smith,et al.  A tutorial on Principal Components Analysis , 2002 .

[30]  Zhengrong Liang,et al.  Automatic centerline extraction for virtual colonoscopy , 2002, IEEE Transactions on Medical Imaging.

[31]  J. Sethian,et al.  Numerical Schemes for the Hamilton-Jacobi and Level Set Equations on Triangulated Domains , 1998 .

[32]  William E. Lorensen,et al.  Marching cubes: A high resolution 3D surface construction algorithm , 1987, SIGGRAPH.

[33]  Tony F. Chan,et al.  Active contours without edges , 2001, IEEE Trans. Image Process..

[34]  Calvin R. Maurer,et al.  A Linear Time Algorithm for Computing Exact Euclidean Distance Transforms of Binary Images in Arbitrary Dimensions , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[35]  Zhengrong Liang,et al.  Haustral Fold Segmentation of CT Colonography Using Ridge Line Detection , 2010, Virtual Colonoscopy and Abdominal Imaging.

[36]  Hans-Peter Seidel,et al.  Ridge-Valley Lines on Meshes via Implicit Surface Fitting , 2004 .

[37]  Zhengrong Liang,et al.  Computer-aided detection of colonic polyps with level set-based adaptive convolution in volumetric mucosa to advance CT colonography toward a screening modality , 2009, Cancer management and research.

[38]  M. Lipschutz.  Schaum's outline of theory and problems of differential geometry : including 500 solved problems completely solved in detail / Martin M. Lipschutz , 1969 .

[39]  Zhengrong Liang,et al.  An EM Approach to MAP Solution of Segmenting Tissue Mixtures: A Numerical Analysis , 2009, IEEE Transactions on Medical Imaging.

[40]  Masahiro Oda,et al.  Haustral fold detection method for CT colonography based on difference filter along colon centerline , 2009, Medical Imaging.

[41]  Zhengrong Liang,et al.  A Coupled Level Set Framework for Bladder Wall Segmentation With Application to MR Cystography , 2010, IEEE Transactions on Medical Imaging.

[42]  P. Pickhardt,et al.  Surface visualization at 3D endoluminal CT colonography: degree of coverage and implications for polyp detection. , 2006, Gastroenterology.

[43]  Burak Acar,et al.  Registration of Supine and Prone CT Colonography Data: Method and Evaluation , 2005 .