Adaptive Shape Prior Constrained Level Sets for Bladder MR Image Segmentation

Three-dimensional bladder wall segmentation for thickness measuring can be very useful for bladder magnetic resonance (MR) image analysis, since thickening of the bladder wall can indicate abnormality. However, it is a challenging task due to the artifacts inside bladder lumen, weak boundaries in the apex and base areas, and complicated outside intensity distributions. To deal with these difficulties, in this paper, an adaptive shape prior constrained directional level set model is proposed to segment the inner and outer boundaries of the bladder wall. In addition, a coupled directional level set model is presented to refine the segmentation by exploiting the prior knowledge of region information and minimum thickness. With our proposed method, the influence of the artifacts in the bladder lumen and the complicated outside tissues surrounding the bladder can be appreciably reduced. Furthermore, the leakage on the weak boundaries can be avoided. Compared with other related methods, better results were obtained on 11 patients' 3-D bladder MR images by using the proposed method.

[1]  J. Sethian,et al.  FRONTS PROPAGATING WITH CURVATURE DEPENDENT SPEED: ALGORITHMS BASED ON HAMILTON-JACOB1 FORMULATIONS , 2003 .

[2]  Chunming Li,et al.  A Level Set Method for Image Segmentation in the Presence of Intensity Inhomogeneities With Application to MRI , 2011, IEEE Transactions on Image Processing.

[3]  Boudewijn P. F. Lelieveldt,et al.  A 3-D Active Shape Model Driven by Fuzzy Inference: Application to Cardiac CT and MR , 2008, IEEE Transactions on Information Technology in Biomedicine.

[4]  Michael Brady,et al.  Fusion of perpendicular anisotropic MRI sequences , 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[5]  Gang Chen,et al.  An Improved Level Set for Liver Segmentation and Perfusion Analysis in MRIs , 2009, IEEE Transactions on Information Technology in Biomedicine.

[6]  B. Hamm,et al.  MR Imaging of the Abdomen and Pelvis , 2009 .

[7]  Dimitris N. Metaxas,et al.  Deformable segmentation via sparse representation and dictionary learning , 2012, Medical Image Anal..

[8]  Ron Kikinis,et al.  Tumor detection in the bladder wall with a measurement of abnormal thickness in CT scans , 2003, IEEE Transactions on Biomedical Engineering.

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

[10]  João Manuel R. S. Tavares,et al.  Novel Approach to Segment the Inner and Outer Boundaries of the Bladder Wall in T2-Weighted Magnetic Resonance Images , 2011, Annals of Biomedical Engineering.

[11]  Guillermo Sapiro,et al.  Geodesic Active Contours , 1995, International Journal of Computer Vision.

[12]  Guopu Zhu,et al.  Directional geodesic active contour for image segmentation , 2007, J. Electronic Imaging.

[13]  Chunming Li,et al.  Distance Regularized Level Set Evolution and Its Application to Image Segmentation , 2010, IEEE Transactions on Image Processing.

[14]  Chunming Li,et al.  Level set evolution without re-initialization: a new variational formulation , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[15]  A. Proietto,et al.  Pelvic anatomy and MRI. , 2006, Best practice & research. Clinical obstetrics & gynaecology.

[16]  Junzhou Huang,et al.  Towards robust and effective shape modeling: Sparse shape composition , 2012, Medical Image Anal..

[17]  Xuelong Li,et al.  Coupled Directional Level Set for MR Image Segmentation , 2012, 2012 11th International Conference on Machine Learning and Applications.

[18]  Sheng Xu,et al.  Adaptively Learning Local Shape Statistics for Prostate Segmentation in Ultrasound , 2011, IEEE Transactions on Biomedical Engineering.

[19]  Xuelong Li,et al.  Segmenting Images by Combining Selected Atlases on Manifold , 2011, MICCAI.

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

[21]  Michael Brady,et al.  Segmentation of the bladder wall using coupled level set methods , 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

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

[23]  Jerry L Prince,et al.  Image Segmentation Using Deformable Models , 2000 .

[24]  Bin Li,et al.  Multiscan MRI-based virtual cystoscopy , 2000, Medical Imaging.