25 Best Books on Medical Image Processing

“Bio-Imaging and Visualization for Patient-Customized Simulations (Lecture Notes in Computational Vision and Biomechanics)” Book Review: The book offers an all-inclusive guide for individuals interested in multidisciplinary fields related to medical imaging, computer vision, and scientific data visualization. It caters to researchers, PhD students, and graduate students with an array of interests, including image processing and analysis, image segmentation, image registration and fusion, image-based modeling, and simulation. The book presents an updated perspective on the latest trends and advancements in these fields, utilizing various methods and techniques such as optimization processes, graphs, hidden Markov models, sensor calibration, fuzzy logic, data mining, cellular automation, active shape models, template matching, and level sets. The author’s objective is to bring together experts from different domains such as Biomechanics, Engineering, Medicine, Mathematics, Physics, and Statistics to share their knowledge and expertise. The book provides an in-depth understanding of topics like Graph-Based Methodology for Volumetric Left Ventricle Segmentation, Minimally Interactive MRI Segmentation for Subject-Specific Modelling of the Tongue, Biomechanical Simulation of Lung Deformation from One CT Scan, and 2D-3D Registration, which is an essential step towards Image-Guided Ankle Fusion.

“Bio-Inspired Computation and Applications in Image Processing” Book Review: This book is an extensive guide for individuals interested in the intersection of medical imaging, computer vision, and scientific data visualization. It is designed for researchers, PhD students, and graduate students with diverse interests in areas such as image processing and analysis, image segmentation, image registration and fusion, image-based modeling, and simulation. The book provides a contemporary outlook on the latest developments and trends in these fields, utilizing a range of methods and techniques including optimization processes, graphs, hidden Markov models, sensor calibration, fuzzy logic, data mining, cellular automation, active shape models, template matching, and level sets. The author aims to bring together experts from various disciplines such as Biomechanics, Engineering, Medicine, Mathematics, Physics, and Statistics to share their knowledge and expertise. With detailed coverage of topics such as Graph-Based Methodology for Volumetric Left Ventricle Segmentation, Minimally Interactive MRI Segmentation for Subject-Specific Modelling of the Tongue, Biomechanical Simulation of Lung Deformation from One CT Scan, and 2D-3D Registration, the book offers a comprehensive understanding of these concepts and techniques, essential for Image-Guided Ankle Fusion.

“Image Processing Techniques for Dental Bio-Metrics” Book Review: The book is an excellent resource for experts in visualization, including those in mathematics, computer science, and bio-medical applications, as well as research students interested in these areas. It provides a detailed overview of recent work using geometric partial differential equations and the level set methodology in medical and biomedical image analysis, covering both traditional applications in medical imagery such as CT, MR, Ultrasound and emerging areas in the life sciences such as confocal microscope image understanding. The book focuses on essential topics such as Geometric Model for Image Analysis in Cytology, Spherical Flattening of the Cortex Surface, and Fast Methods for Shape Extraction in Medical and Biomedical Imaging, providing critical insights for researchers and practitioners alike.

“Geometric Methods in Bio-Medical Image Processing (Mathematics and Visualization)” Book Review: This book is an essential resource for experts in visualization, including those in mathematics, computer science, and bio-medical applications, as well as research students interested in these fields. It covers recent developments using geometric partial differential equations and the level set methodology in medical and biomedical image analysis, providing an overview of traditional applications in medical imagery such as CT, MR, and Ultrasound, and exploring emerging areas in the life sciences such as confocal microscope image understanding. The book delves into important topics such as Geometric Model for Image Analysis in Cytology, Spherical Flattening of the Cortex Surface, and Fast Methods for Shape Extraction in Medical and Biomedical Imaging, shedding light on key concepts and techniques that are critical for researchers and practitioners.

“Advances in Bio-Imaging: From Physics to Signal Understanding Issues: State-of-the-Art and Challenges (Advances in Intelligent and Soft Computing)” : Book Review: This book aims to bridge the gap between bio imaging and other fields of research such as Chemistry, Physics, Mathematics, and Computer Sciences. It provides an overview of recent advances in the field of bio imaging while also highlighting the limitations that must be addressed to design fully integrated BioImaging Devices. The book equips learners with the tools and knowledge necessary to apply bio imaging and solve the new challenges that life scientists encounter daily. It includes chapters covering topics such as Persistent Luminescence Nanoparticles for Bioimaging, Automated Identification and Analysis of Visual Micro-experiments on Cellular Microarray, Intravital Multiphoton Imaging of Immune Cells, and Functional MRI of Neural Plasticity and Drug Effect in the Brain.

“Advances in Face Image Analysis:: Theory and applications” Book Review: This book is aimed at professionals and researchers in the field of face image analysis, as well as anyone interested in extracting features from face images and the latest concepts in facial image recognition. It presents various approaches to analyzing and recognizing faces. The topics covered include automatic face detection, fitting 3D face models, robust face recognition, recognizing facial expressions, embedding data in face images, estimating 3D face pose without models, and estimating age from images. The book provides detailed explanations of computer vision and pattern recognition methods used for analyzing facial data. It also offers insights into the advancements, challenges, and opportunities in automatic facial expression recognition.

“Biomedical Image Analysis: Statistical and Variational Methods” Book Review: The latest and most efficient techniques in image analysis are thoroughly explained in this book. The book encompasses various topics such as segmentation, registration, and visualization algorithms, along with their applications in the fields of computer vision, imaging, and computational biomedical science. The book covers a range of topics, including signals, systems, image formation, modality, stochastic models, computational geometry, level set methods, CAD models, as well as mathematical and statistical concepts. This book relates theory to practical instances in x-ray, ultrasound, nuclear medicine, MRI, and CT imaging, making the models more concrete and tangible.

“Applied Medical Image Processing, Second Edition: A Basic Course” Book Review: This book is a comprehensive introduction to image processing in medicine, focusing on its clinical significance and unique demands. It avoids excessive mathematical complexities and instead presents the principles through practical implementation of algorithms using simple MATLAB / Octave scripts. The book includes image data and illustrations that can be accessed through a CD-ROM or website. It covers the physics behind medical image processing and explores topics such as image formats, data storage, intensity transformations, image filtering, and applications of the Fourier transform. Additionally, the book delves into advanced concepts like three-dimensional spatial transforms, volume rendering, image registration, and tomographic reconstruction.

“Image Processing with MATLAB: Applications in Medicine and Biology (MATLAB Examples)” Book Review: This book explores the field of image processing and analysis, providing valuable MATLAB codes and functions. It covers essential topics such as probability and statistics, two-dimensional fast Fourier transform, and nonlinear diffusion filtering. The book also discusses image denoising techniques based on partial differential equations (PDEs) and introduces intensity-based image segmentation methods. It delves into various techniques like thresholding, K-means clustering, and fuzzy C-means clustering. Additionally, the book explores markov random field (MRF)-based image segmentation, boundary and curvature analysis, as well as parametric and geometric deformable models. It showcases three specific applications of image processing and analysis and offers problem-solving approaches in medicine and biology.

“Biosignal and Medical Image Processing” Book Review: This book is suitable for undergraduate courses and students from various disciplines. It aims to provide a comprehensive understanding of image processing, enabling readers to apply the concepts intelligently. The book incorporates the necessary mathematical principles as needed and explores signal and image processing concepts using the MATLAB software package and its toolboxes. It offers a detailed exploration of the subject and is inspired by the latest trends in biomedical engineering education. Additionally, students from other disciplines can also benefit from gaining practical knowledge in signal and image processing through this book.

“ECG Signal Processing, Classification and Interpretation: A Comprehensive Framework of Computational Intelligence” Book Review: The book explores different approaches of computational intelligence, which can be used individually or in combination. It provides a comprehensive framework for extracting valuable information from ECG signals. This self-contained book covers concepts, methodologies, algorithms, and case studies, addressing various applications. It is divided into parts that introduce the fundamental ideas of computational intelligence. The book discusses data acquisition, morphology, and their diagnostic applications. It also presents techniques and models of computational intelligence suitable for signal processing. Detailed ECG system-diagnostic interpretation and knowledge acquisition architectures are included. The book contains illustrative materials such as numerical experiments, schemes, exercises, and advanced problems to enhance understanding.

“Biomedical Image Analysis and Machine Learning Technologies: Applications and Techniques (Premier Reference Source)” Book Review: This book explores the foundational role of medical images in routine clinical decisions, with their growing influence across various medical disciplines. It delves into the realm of biomedical image analysis and machine learning technologies. The book showcases a wide array of applications and techniques that offer a comprehensive view of the intricate interplay between biomedical complexity and medical imaging. Serving as a pioneering industry reference, this innovative publication also sparks creativity by presenting novel ideas for addressing medical challenges. It is a valuable resource for professionals seeking to explore the practical applications of medical issues.

“High-Throughput Image Reconstruction and Analysis” Book Review: This book caters to graduate students in bioinformatics or biomedical engineering and offers valuable insights for professionals in cell biology, microscope manufacturing, HPC development, and drug discovery. It delves into the coupling of high-performance computing (HPC) and explores how automated imaging techniques can revolutionize our understanding of complex biological systems. By providing an integrated perspective on technology-driven advancements in science, the book highlights the advantageous use of HPC to create and analyze intricate models derived from extensive biological datasets. Each topic is backed by research, striking a balance between theoretical explanations and real-world case studies.

“Biomedical Image Segmentation: Advances and Trends” Book Review: This book focuses on the crucial role of image segmentation in biomedical imaging for accurate diagnosis and quantitative analysis. It explores a wide range of imaging techniques and discusses their physical principles and unique characteristics, including noise modeling that may necessitate modality-specific algorithms. With significant advancements in biomedical image segmentation, this book addresses the specific challenges involved in this field. It provides an overview of advanced segmentation algorithms and their applications, equipping readers with a comprehensive understanding of cutting-edge techniques in biomedical image segmentation.

“Applied Medical Image Processing: A Basic Course” Book Review: This book presents real-life applications in a tangible and accessible manner, drawing on the authors’ clinical environments and extensive teaching experience in applied medical image processing. The basic course covers the fundamental methods in applied image processing, going beyond basic applied mathematics, physics, and programming. Simple, well-commented MATLAB® examples illustrate the concepts. The book highlights the rapid evolution of radiological imaging in medical image processing and its crucial role in modern diagnostics and the actual treatment of diseases. It introduces the basic image processing algorithms used in clinical routine applications and bridges the gap between basic engineering knowledge, such as simple programming and applied mathematics. Additionally, it offers a general understanding of a science that impacts the health of a broad public.

“Biomedical Image Understanding: Methods and Applications (Wiley Series in Biomedical Engineering and Multi–Disciplinary Integrated Systems.)” Book Review: The focus of this book is on image understanding and semantic interpretation, covering various aspects such as image processing, filtering, enhancement, de-noising, restoration, reconstruction, segmentation, feature extraction, registration, clustering, pattern classification, and data fusion. It also delves into important clinical applications such as virtual colonoscopy, ocular disease diagnosis, and liver tumor detection, providing case studies, diagrams, and illustrations. With a comprehensive set of signal and image processing tools, this book is a crucial resource for research and applications in biomedical image understanding. It includes diagnostic decision-making tools and classification methods, as well as nonlinear methods for describing and classifying signals, such as entropy-based and scaling methods.

“Guide to Medical Image Analysis: Methods and Algorithms (Advances in Computer Vision and Pattern Recognition)” Book Review: This book is a valuable resource for practitioners, computer scientists, electrical engineers, and students of medical image processing and analysis. It covers a range of topics including imaging techniques, reconstruction techniques, and image artifacts. The book also delves into various techniques for image enhancement, feature detection, feature generation, segmentation, registration, and validation. Deep convolutional networks are used for segmentation and labeling tasks. Additionally, the book provides information on Markov random field optimization, variational calculus, and principal component analysis. To aid in learning, each chapter includes exercise questions at the end.

“Advances in Low-Level Color Image Processing (Lecture Notes in Computational Vision and Biomechanics)” Book Review: This book covers advancements in digital color imaging and computer hardware technology, including topics such as medical imaging, content-based image retrieval, biometrics, and watermarking. It also covers digital inpainting, remote sensing, and visual quality inspection. Additionally, the book provides an introduction to the color image processing pipeline.

“Advanced Algorithmic Approaches to Medical Image Segmentation” Book Review: This book focuses on medical imaging, which is essential for diagnosis and patient care. It provides information on various imaging modalities such as X-rays, computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound. The book also explains the model-based segmentation techniques used for cardiac, brain, breast, and microscopic cancer cell imaging.

“Advances in Computational Vision and Medical Image Processing” Book Review: This book covers recent developments in computational vision and medical image processing. It explains how mathematics, statistics, psychology, mechanics, and physics are utilized in computational vision. The book delves into various topics, including shape reconstruction, segmentation, registration, behavior interpretation and simulation, motion and deformation analysis, virtual reality, and tissue characterization in modeling.

“Medical Image Processing Concepts and Applications” Book Review: This book is a useful reference for undergraduate and postgraduate students of biomedical engineering, computer science engineering, and IT. It covers topics such as biomedical image processing, medical image restoration, biomedical image segmentation, and soft computing techniques. The book provides an overview of noise reduction filters for medical images, as well as feature extraction and statistical measurement. Additionally, it explains the morphological operations commonly used in medical image processing.

“Handbook of Medical Image Processing and Analysis (Academic Press Series in Biomedical Engineering)” Book Review: This book is a valuable resource for biomedical engineers, researchers, and professionals in the field of medical imaging and medical image processing. It covers various techniques used for processing and analyzing medical images. The book explains the use of higher-order statistics for tissue segmentation and growth modeling in oncological image analysis, as well as the analysis of cell nuclear features in fluorescence microscopy images. Additionally, the book discusses imaging and communication in medical and public health informatics, including dynamic mammogram retrieval from web-based image libraries.

“Digital Image Processing for Medical Applications South Asian Edition” Book Review: This book is a comprehensive guide designed for South Asian readers. Written by Geoff Dougherty, this book covers a wide range of topics related to digital image processing in the context of medical applications. The chapters delve into areas such as image acquisition, image enhancement, image restoration, image segmentation, feature extraction, and image classification. With a focus on South Asian perspectives, the book provides valuable insights and practical techniques for medical professionals, researchers, and students in the field. It serves as an essential resource for understanding and applying digital image processing techniques in medical imaging.

“Spectral and Shape Analysis in Medical Imaging: First International Workshop” Book Review: This book is intended for undergraduate students of structural engineering and can also serve as a reference for working professionals. It compiles a collection of research papers in the field of medical imaging, covering topics such as shape and spectral analysis. The book features refereed proceedings from a conference workshop and reviews concepts such as longitudinal, spectral, and shape methods. The book is enhanced by numerous scientific diagrams and real-life case studies that simplify the presented concepts.