<p><span>The application of machine learning is growing exponentially into every branch of business and science, including medical science. This book presents the integration of machine learning (ML) and deep learning (DL) algorithms that can be applied in the healthcare sector to reduce the time re
Machine Learning and Deep Learning Techniques for Medical Image Recognition
β Scribed by Ben Othman Soufiene, Chinmay Chakraborty
- Publisher
- CRC Press
- Year
- 2024
- Tongue
- English
- Leaves
- 269
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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.
Features
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.
β¦ Table of Contents
Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Preface
About the Editors
Contributors
Chapter 1 Medical Image Detection and Recognition Using Machine Learning and Deep Learning
Chapter 2 Multiple Lung Disease Prediction Using X-Ray Images Based on Deep Convolutional Neural Networks
Chapter 3 Analysis of Machine Learning and Deep Learning in Health Informatics, and Their Application
Chapter 4 Automated Acute Lymphoblastic Leukemia Detection Using Blood Smear Image Analysis
Chapter 5 Smart Digital Healthcare Solutions Using Medical Imaging and Advanced AI Techniques
Chapter 6 Efficient and Fast Lung Disease Predictor Model
Chapter 7 Artificial Intelligence Used to Recognize Fetal Planes Based on Ultrasound Scans during Pregnancy
Chapter 8 Artificial Intelligence Techniques for Cancer Detection from Medical Images
Chapter 9 Handling Segmentation and Classification Problems in Deep Learning for Identification of Interstitial Lung Disease
Chapter 10 Computer Vision Approaches in Radiograph Image Analysis
Chapter 11 Deep Learning Methods for Brain Tumor Segmentation
Chapter 12 Face Mask Detection and Temperature Scanning for the COVID-19 Surveillance System Based on Deep Learning Models
Chapter 13 Diabetic Disease Prediction Using Machine Learning Models and Algorithms for Early Classification and Diagnosis Assessment
Chapter 14 Defeating Alzheimerβs: AI Perspective from Diagnostics to Prognostics
Index
π SIMILAR VOLUMES
<p>The book discusses varied topics pertaining to advanced or up-to-date techniques in medical imaging using artificial intelligence (AI), image recognition (IR) and machine learning (ML) algorithms/techniques. Further, coverage includes analysis of chest radiographs (chest x-rays) via stacked gener
<p>Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep l
</header><div itemprop="description" class="collapsable text"><P>Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learn
<p><i>Machine Learning and Medical Imaging</i> presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent bre
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