Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis

This comprehensive book, written by renowned author Nilanjan Dey, provides a detailed overview of the latest advances in classification techniques for medical image analysis and computer-aided diagnosis (CAD) systems design. The book is specifically designed for researchers and biomedical engineers in the fields of machine learning, deep learning, data analysis, and data management.

Image Classification Problems and Pattern Recognition Methods

The book delves into several complex image classification problems using pattern recognition methods, including:

• Artificial Neural Networks (ANN)
• Support Vector Machines (SVM)
• Bayesian Networks (BN)
• Deep learning

Additionally, the book explores numerous data mining techniques that have proven to be effective classifiers for medical images.

Methodology of Medical Image Classification

The book examines the methodology of medical image classification, covering the taxonomy of both supervised and unsupervised models, algorithms, applications, and challenges.

Recent Advances in Artificial Neural Networks, Machine Learning, and Deep Learning

The book discusses recent advances in Artificial Neural Networks, machine learning, and deep learning in clinical applications, providing researchers and biomedical engineers with valuable insights into the latest developments in the field.

Medical Image Processing and Analysis for CAD Systems Design

The book introduces several techniques for medical image processing and analysis for CAD systems design, making it an essential resource for anyone involved in medical image analysis and diagnosis.

Published by Elsevier Science in July 2019, this book is a must-have for anyone working in the fields of machine learning, deep learning, data analysis, and data management. The book is written in English and has an ISBN of 9780128180044 (hardcover) and 9780128180051 (e-book).