Contour Detection of Mammogram Masses Using ChanVese Model and B-Spline Approximation

ChanVese model segmentation has been applied for contour detection of mass region in mammogram in our previous work. Available information of the desired object contour is used, in this paper, for B-spline approximation. The mass region boundary (contour) is thereafter approximated by a B-spline curve. This approach allows synthesizing the shape of the suspected mass appearing in the mammogram. Experimental results show the accurateness of mass region contour in mammograms using B-spline approximation.

[1]  L. Clarke,et al.  Image segmentation in digital mammography: comparison of local thresholding and region growing algorithms. , 1992, Computerized Medical Imaging and Graphics.

[2]  Robert J. Schalkoff,et al.  Pattern recognition - statistical, structural and neural approaches , 1991 .

[3]  Wilhelm Burger,et al.  Digital Image Processing - An Algorithmic Introduction using Java , 2008, Texts in Computer Science.

[4]  Mph Radhika A. Ramanan MD,et al.  Decision making and counseling around mammography screening for women aged 80 or older , 2007, Journal of General Internal Medicine.

[5]  Akram Aldroubi,et al.  B-SPLINE SIGNAL PROCESSING: PART I-THEORY , 1993 .

[6]  Gwo Giun Lee,et al.  On Digital Mammogram Segmentation and Microcalcification Detection Using Multiresolution Wavelet Analysis , 1997, CVGIP Graph. Model. Image Process..

[7]  Kannan,et al.  ON IMAGE SEGMENTATION TECHNIQUES , 2022 .

[8]  Thomas Hofmann,et al.  Pattern Recognition, Statistical , 2006 .

[9]  Ian W. Ricketts,et al.  The Mammographic Image Analysis Society digital mammogram database , 1994 .

[10]  Carlo Ciulla Improved Signal and Image Interpolation in Biomedical Applications: The Case of Magnetic Resonance Imaging (Mri) , 2009 .

[11]  Farzin Mokhtarian,et al.  A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

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

[13]  Heng-Da Cheng,et al.  A novel approach to microcalcification detection using fuzzy logic technique , 1998, IEEE Transactions on Medical Imaging.

[14]  Azriel Rosenfeld,et al.  Computer Vision , 1988, Adv. Comput..

[15]  N. Obuchowski,et al.  Quantitative classification of breast tumors in digitized mammograms. , 1996, Medical physics.

[16]  YoussefBenYoussef,et al.  Segmentation of Mass Region in Abnormal Mammogram Using Deformable Model , 2014 .

[17]  Vijay K. Jain,et al.  Markov random field for tumor detection in digital mammography , 1995, IEEE Trans. Medical Imaging.

[18]  P. Undrill,et al.  The use of texture analysis to delineate suspicious masses in mammography. , 1995, Physics in medicine and biology.

[19]  Michael Isard,et al.  Active Contours , 2000, Springer London.

[20]  G. Hortobagyi,et al.  Mammography before diagnosis among women age 80 years and older with breast cancer. , 2008, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[21]  Philippe Saint-Marc,et al.  B-spline Contour Representation and Symmetry Detection , 1990, IEEE Trans. Pattern Anal. Mach. Intell..