Segmentation and Classification Methods Of Mammograms: A Case Study
J. Kamal Vijetha, S. Sridevi Sathya Priya · 2022 6th International Conference on Devices, Circuits and Systems (ICDCS) · 2022
Now-a-days most of the women are suffering with various types of cancers, among those Breast cancer is the major one with high mortality rate.This abnormality intends accurate and timely diagnosis so that the possibility of survival of the patient increases. Mammogram images are one of the key tools in visualizing various types of breast cancers. Automatic detection of mass regions and classification of these regions is still a challenging task in research domain which plays a vital role in predicting the severity of the disease and options for better treatment. Several Computer Aided diagnostic (CAD) systems deploying computer vision algorithms were proposed to perform this activity however the advent of deep Neural networks in recent times have increased the pave for conducting research in this domain. This work also presents a case study on classification methods that are used for classifying the type and severity of the disease as one of the major cause for high mortality rate in women in recent times.