Affiliation:
1. Division of Computer Science and Engineering, School of Engineering, CUSAT, Cochin, India
Abstract
Abstract:
Machine Learning (ML) plays an essential part in the research area of medical image processing.
The advantages of ML techniques lead to more intelligent, accurate, and automatic computeraided
detection (CAD) systems with improved learning capability. In recent years, deep learning-based
ML approaches developed to improve the diagnostic capabilities of CAD systems. This study reviews
image enhancement, ML and DL methods for breast cancer detection and diagnosis using mammogram
images and provides an overview of these methods. The analysis of different ways of ML and
DL shows that the usages of traditional ML approaches are limited. However, DL techniques have an
excellent future for implementing medical image analysis and improving the ability to exist CAD systems.
Despite the significant advancements in deep learning methods for analyzing medical images to
detect breast cancer, challenges still exist regarding data quality, computational cost, and prediction
accuracy.
Publisher
Bentham Science Publishers Ltd.
Subject
Radiology, Nuclear Medicine and imaging