Mammographic image segmentation by marker controlled watershed algorithm
Arnab Chattaraj, Arpita Das, Mahua Bhattacharya · 2017
Breast cancer is one of the major causes of death among women around the world. To diagnose this disease using mammography technique, segmentation is an important step to detect the suspicious region(s) of mammograms. Segmentation concerns to the process of division of mammograms into different sections. Objective of segmentation is to simply modify the presentation of an image so that it becomes more significant and easier to study. Although many algorithms have been proposed yet to segment out the suspicious regions of mammograms, automatic segmentation of masses of improved quality is still considered to be difficult. This study introduces a novel marker controlled watershed algorithm for segmentation of mammograms to highlight the suspicious regions more distinctly. It is a morphological operation on the basis of obtaining watershed lines from a topographic demonstration of the input image. The proposed method has been applied and examined on various difficult to diagnose mammograms taken from MIAS & BIRADS database. Results obtained by this technique are impressive for qualitative analysis and also approved by the radiologists.