Advances in Deep Learning for Medical Image Analysis

ISBN-13: 9781032137162 / Angielski / Twarda / 2022 / 154 str.

Archana Mire; Vinayak Elangovan; Shailaja Patil

Opis

This reference text covers deep learning methods for detection of various diseases and analysis of medical images for better understanding. It will serve as a useful text for graduate students and academic researchers in the fields of electronics engineering, computer science, biomedical engineering, and electrical engineering.

Spis treści

1. ANFIS BASED CARDIAC ARRHYTHMIA CLASSIFICATION 2. TWO-STAGE DEEP LEARNING ARCHITECTURE FOR CHEST X-RAY BASED COVID-19 PREDICTION 3. WHITE BLOOD CELLS CLASSIFICATION USING CONVENTIONAL AND DEEP LEARNING TECHNIQUES: A COMPARATIVE STUDY 4. COMPARISON AND PERFORMANCE EVALUATION USING CONVOLUTION NEURAL NETWORK BASED DEEP LEARNING MODELS FOR SKIN CANCER IMAGE CLASSIFICATION 5. A REVIEW ON BREAST CANCER DETECTION USING DEEP LEARNING TECHNIQUES 6. ARTIFICIAL INTELLIGENCE & MACHINE LEARNING: A SMART SCIENCE APPROACH FOR CANCER CONTROL 7. DETECTION OF DIABETIC FOOT ULCER USING MACHINE/ DEEP LEARNING 8. REVIEW ON DEEP LEARNING TECHNIQUES FOR PROGNOSIS AND MONITORING OF DIABETES MELLITUS