1st Edition

Machine Learning and Deep Learning Techniques for Medical Image Recognition

Edited By Ben Othman Soufiene, Chinmay Chakraborty Copyright 2024
    270 Pages 119 B/W Illustrations
    by CRC Press

    Machine Learning and Deep Learning Techniques for Medical Image Recognition comprehensively reviews deep learning-based algorithms in medical image analysis problems including medical image processing. It includes a detailed review of deep learning approaches for semantic object detection and segmentation in medical image computing and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks with the theory and varied selection of techniques for semantic segmentation using deep learning principles in medical imaging supported by practical examples.


    • Offers important key aspects in the development and implementation of machine learning and deep learning approaches toward developing prediction tools and models and improving medical diagnosis                                       
    • Teaches how machine learning and deep learning algorithms are applied to a broad range of application areas, including chest X-ray, breast computer-aided detection, lung and chest, microscopy, and pathology
    • Covers common research problems in medical image analysis and their challenges                         
    • Focuses on aspects of deep learning and machine learning for combating COVID-19                         
    • Includes pertinent case studies                                                                                                            

    This book is aimed at researchers and graduate students in computer engineering, artificial intelligence and machine learning, and biomedical imaging.

    Chapter 1 Medical Image Detection and Recognition Using Machine Learning and Deep Learning
    M Arun Anoop, P Karthikeyan, and S Poonkuntran

    Chapter 2 Multiple Lung Disease Prediction Using X-Ray Images Based on Deep Convolutional Neural Networks
    Nagarjuna Telagam, Nehru Kandasamy, Kumar Raja, Tharuni Gelli, and D Ajitha

    Chapter 3 Analysis of Machine Learning and Deep Learning in Health Informatics, and Their Application
    Tharuni Gelli , Challa Sri Gouri, D Ajitha, Nagarjuna Telagam, and Ben Othman Soufiene

    Chapter 4 Automated Acute Lymphoblastic Leukemia Detection Using Blood Smear Image Analysis
    Chandan Kumar Jha, Arvind Choubey, Maheshkumar H Kolekar, and Chinmay Chakraborty
    Chapter 5 Smart Digital Healthcare Solutions Using Medical Imaging and Advanced AI Techniques
    P Divyashree and Priyanka Dwivedi

    Chapter 6 Efficient and Fast Lung Disease Predictor Model
    Abdelbaki Souid, Hamroun Mohamed, Ben Othman Soufiene, and Hedi Sakli

    Chapter 7 Artificial Intelligence Used to Recognize Fetal Planes Based on Ultrasound Scans during Pregnancy
    Haifa Ghabri, Ben Othman Soufiene, and Hedi Sakli

    Chapter 8 The Artificial Intelligence Techniques for Cancer Detection from Medical Images
    Rabiaa Tbibe, Ben Othman Soufiene, Chinmay Chakraborty, and Hedi Sakli

    Chapter 9 Handling Segmentation and Classification Problems in Deep Learning for Identification of Interstitial Lung Disease
    Tapas Pal, Biswadev Goswami, and Rajesh P Barnwal

    Chapter 10 Computer Vision Approaches in Radiograph Image Analysis: A Targeted Review of Current Progress, Challenges, and Future Perspectives
    Abdelbaki Souid, Ben Othman Soufiene, and Hedi Sakli

    Chapter 11 Deep Learning Methods for Brain Tumor Segmentation
    Marwen Sakli, Chaker Essid, Bassem Ben Salah, and Hedi Sakli

    Chapter 12 Face Mask Detection and Temperature Scanning for the COVID-19 Surveillance System Based on Deep Learning Models
    Nagarjuna Telagam, D Ajitha, Nehru Kandasamy, and Ben Othman Soufiene

    Chapter 13 Diabetic Disease Prediction Using Machine Learning Models and Algorithms for Early Classification and Diagnosis Assessment
    AAA Aayush, Jawahar Sundaram, S Devaraju, Sujith Jayaprakash, Harishchander Anandaram, and C Manivasagan

    Chapter 14 Defeating Alzheimer's: AI Perspective from Diagnostics to Prognostics: Literature Summary
    Iheb Elghaieb, Abdelbaki Souid, Ahmed Zouinkhi, and Hedi Sakli



    Ben Othman Soufiene was Assistant Professor of computer science at the University of Gabes, Tunisia, from 2016 to 2021. He received his PhD in computer science from Manouba University in 2016 for his dissertation on secure data aggregation in wireless sensor networks. He also earned an MS from Monastir University in 2012. His research interests focus on the Internet of Medical Things, wireless body sensor networks, wireless networks, artificial intelligence, machine learning, and big data.

    Chinmay Chakraborty is Assistant Professor in the Department of Electronics and Communication Engineering, BIT Mesra, India, and a Postdoctoral Fellow of the Federal University of PiauĂ­, Brazil. His primary areas of research include wireless body area networks, Internet of Medical Things (IoMT), point-of-care diagnosis, mHealth/e-health, and medical imaging. Chakraborty is the co-editor of many books on Smart IoMT, healthcare technology, and sensor data analytics.