Morphological Method of Microcalcifications Detection in Mammograms

Detection of microcalcifications (MCs) in mammograms for early breast can- cer diagnosing is a widely investigated subject. A number of methods have been tried out so far, but obtained results are still not satisfactory. To avoid difficulties with comparisons of our results with others', we present results ob- tained on mammograms from the Digital Database for Screening Mammography (DDSM), provided by the University of South Florida. In this study, a novel ap- proach to MCs detection based on mathematical morphology is presented. A combination of methods is used for the detection of MCs. The evaluation of the proposed technique is done using a free-response operating characteristic (FROC). Our results demonstrate that the MCs can be effectively detected by the proposed approach.

[1]  Heng-Da Cheng,et al.  Microcalcification detection using fuzzy logic and scale space approaches , 2004, Pattern Recognit..

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

[3]  A Bazzani,et al.  An SVM classifier to separate false signals from microcalcifications in digital mammograms , 2001, Physics in medicine and biology.

[4]  Nikolas P. Galatsanos,et al.  A support vector machine approach for detection of microcalcifications , 2002, IEEE Transactions on Medical Imaging.

[5]  K. Drouiche,et al.  Highly regular wavelets for the detection of clustered microcalcifications in mammograms , 2003, IEEE Transactions on Medical Imaging.

[6]  E Alberdi,et al.  A comparative study of four techniques for calcification detection , 2001 .

[7]  Mariusz Nieniewski Morphological method for extraction of microcalcifications in mammograms for breast cancer diagnosis , 1999 .

[8]  Michel Bruynooghe,et al.  Detection of very subtle microcalcification clusters in high resolution full field X-ray mammograms , 2003 .

[9]  Marios A Gavrielides,et al.  Parameter optimization of a computer-aided diagnosis scheme for the segmentation of microcalcification clusters in mammograms. , 2002, Medical physics.

[10]  Dev P. Chakraborty,et al.  The FROC, AFROC and DROC Variants of the ROC Analysis , 2000 .

[11]  Heinz-Otto Peitgen,et al.  Scale-space signatures for the detection of clustered microcalcifications in digital mammograms , 1999, IEEE Transactions on Medical Imaging.