A Survey on the Preprocessing Techniques of Mammogram for the Detection of Breast Cancer

The aim of this paper is to review existing approaches of preprocessing in mammographic images. The objective of preprocessing is to improve the quality of the image and make it ready for further processing by removing the irrelevant noise and unwanted parts in the background of the mammogram. There are different of methods of preprocessing a mammogram image. Their advantages and disadvantages are discussed.

[1]  J. Harvey,et al.  Breast cancer—facts and figures , 2013 .

[2]  Baba C. Vemuri,et al.  Shape Modeling with Front Propagation: A Level Set Approach , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Sumit Chopra,et al.  Segmentation of the Mammogram Images to find Breast Boundaries , 2011 .

[4]  Luc Vincent,et al.  Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  K. Ramar,et al.  Histogram Modified Local Contrast Enhancement for mammogram images , 2011, Appl. Soft Comput..

[6]  Dr. V. Saravanan.  A Novel Approach for Cancer Detection in MRI Mammogram Using Decision Tree Induction and BPN , 2011 .

[7]  H. Chenga,et al.  Automated breast cancer detection and classification using ultrasound images A survey , 2009 .

[8]  D. Cavouras,et al.  AN EFFICIENT CLAHE-BASED , SPOT-ADAPTIVE , IMAGE SEGMENTATION TECHNIQUE FOR IMPROVING MICROARRAY GENES ’ QUANTIFICATION , 2007 .

[9]  Samir Kumar Bandyopadhyay,et al.  Technique for preprocessing of digital mammogram , 2012, Comput. Methods Programs Biomed..

[10]  Joseph Y. Lo,et al.  Mutual information-based template matching scheme for detection of breast masses: From mammography to digital breast tomosynthesis , 2011, J. Biomed. Informatics.

[11]  Koichi Harada,et al.  Breast Skin-Line Estimation and Breast Segmentation in Mammograms using Fast-Marching Method , 2007 .

[12]  Heng-Da Cheng,et al.  Computer-aided detection and classification of microcalcifications in mammograms: a survey , 2003, Pattern Recognit..

[13]  Naseem Rao,et al.  Semi Automatic Segmentation of Breast Cancer for Mammograms Based on Watershed Segmentation , 2011 .

[14]  Samir Brahim Belhaouari,et al.  Breast cancer diagnosis in digital mammogram using multiscale curvelet transform , 2010, Comput. Medical Imaging Graph..

[15]  Rangaraj M. Rangayyan,et al.  Analysis of asymmetry in mammograms via directional filtering with Gabor wavelets , 2001, IEEE Transactions on Medical Imaging.

[16]  M. Hanmandlu,et al.  A comparison of two methods for the segmentation of masses in the digital mammograms , 2010, Comput. Medical Imaging Graph..

[17]  Essam A. Rashed,et al.  Multiresolution mammogram analysis in multilevel decomposition , 2007, Pattern Recognit. Lett..

[18]  H. Damasio,et al.  IEEE Transactions on Pattern Analysis and Machine Intelligence: Special Issue on Perceptual Organization in Computer Vision , 1998 .

[19]  Shi-Jinn Horng,et al.  A new computation of shape moments via quadtree decomposition , 2000, Pattern Recognit..

[20]  K Thangavel..  Mammogram Mining with Genetic Optimization of Ant-Miner Parameters , 2009 .

[21]  Ruola Ning,et al.  Breast volume denoising and noise characterization by 3D wavelet transform. , 2004, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[22]  Samir Kumar Bandyopadhyay,et al.  Pre-processing of Mammogram Images , 2010 .

[23]  Asst. Professor,et al.  Medical Image Feature , Extraction , Selection And Classification , 2022 .

[24]  Farrukh Nagi,et al.  Automated breast profile segmentation for ROI detection using digital mammograms , 2010, 2010 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES).

[25]  Samir Kumar Bandyopadhyay,et al.  Accurate Breast Contour Detection Algorithms in Digital Mammogram , 2011 .

[26]  Nico Karssemeijer,et al.  Single and multiscale detection of masses in digital mammograms , 1999, IEEE Transactions on Medical Imaging.