- Bio-Image Processing
- Biomedical Image Processing and Interpretation
- Advance Medical Image Processing
1. Bio-Image Processing
|1."Bio-Imaging and Visualization for Patient-Customized Simulations (Lecture Notes in Computational Vision and Biomechanics)" by João Manuel R S Tavares and Xiongbiao Luo|
“Bio-Imaging and Visualization for Patient-Customized Simulations (Lecture Notes in Computational Vision and Biomechanics)” : Book Review: The book is an ideal guide for researchers, PhD students, and graduate students with multidisciplinary interests related to the areas of medical imaging, image processing and analysis, computer vision, image segmentation, image registration and fusion, scientific data visualization, and image based modeling and simulation. The book includes new trends in those fields, using several methods and techniques, including the finite element method, similarity metrics, optimization processes, graphs, hidden Markov models, sensor calibration, fuzzy logic, data mining, cellular automation, active shape models, template matching and level sets. The book aims at bringing together together researchers representing several fields, such as Biomechanics, Engineering, Medicine, Mathematics, Physics and Statistic.The book covers chapters 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: A Step Towards Image-Guided Ankle Fusion in great detail.
|2."Bio-Inspired Computation and Applications in Image Processing" by João Paulo Papa and Xin-She Yang Professor|
“Bio-Inspired Computation and Applications in Image Processing” : Book Review: The book explains the latest developments in bio-inspired computation in image processing, focusing on nature-inspired algorithms that are linked with deep learning that have recently emerged in the field .It mentions the latest developments in bio-inspired computation in image processing. The book also features the introduction and analysis of the key bio-inspired methods and techniques. It covers the theoretical aspect as well as the practical aspect of the subject. The book contains a number of complex problems in image and signal processing which help learners to incorporate their theoretical knowledge in real world applications.The book also includes future research trends in bio-inspired computation, helping researchers establish possible new research avenues to pursue.
|3."Image Processing Techniques for Dental Bio-Metrics" by Parmar Shaishavkumar and Amin Mehulkumar|
|4."Geometric Methods in Bio-Medical Image Processing (Mathematics and Visualization)" by imusti|
“Geometric Methods in Bio-Medical Image Processing (Mathematics and Visualization)” Book Review: The book is an ideal guide for visualization experts in mathematics, computer science and bio-medical applications and to research students on above topics. The book includes recent work using geometric partial differential equations and the level set methodology in medical and biomedical image analysis. It gives an overview on traditional applications in medical imagery such as, CT, MR, Ultrasound. It also features applications in the area of Life Sciences, such as confocal microscope image understanding.The book throws light on some important topics like Geometric Model for Image Analysis in Cytology, Spherical Flattening of the Cortex Surface and Fast Methods for Shape Extraction in Medical and Biomedical Imaging.
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|6."Advances in Bio-Imaging: From Physics to Signal Understanding Issues: State-of-the-Art and Challenges (Advances in Intelligent and Soft Computing)" by Alexandre Gouaillard and Nicolas Loménie|
“Advances in Bio-Imaging: From Physics to Signal Understanding Issues: State-of-the-Art and Challenges (Advances in Intelligent and Soft Computing)” : Book Review: The book aims at integrating bio imaging with other fields of research like Chemistry, Physics, Mathematics and Computer Sciences.The book highlights the recent advances in the field of bio imaging and also lists out the limitations that need to be addressed to design fully integrated BioImaging Device. The book enables the learners to use bio imaging and solve the new challenges that life scientists provide on a daily basis. It includes chapters like 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.
|7."Advances in Face Image Analysis:: Theory and applications" by Fadi Dornaika|
“Advances in Face Image Analysis:: Theory and applications” Book Review: The book is designed for researchers and professionals working in the field of face image analysis, the entire pattern recognition community interested in processing and extracting features from raw face images, and technical experts as well as postgraduate computer science students interested in cutting edge concepts of facial image recognition. It provides several approaches to facial image analysis and recognition. The book includes topics like automatic face detection, 3D face model fitting, robust face recognition, facial expression recognition, face image data embedding, model-less 3D face pose estimation and image-based age estimation. The book covers computer vision and pattern recognition methods used to analyze facial data in great detail.It also offers an overview on Advances, Challenges, and Opportunities in Automatic Facial Expression Recognition.
2. Biomedical Image Processing and Interpretation
|1."Biomedical Image Analysis: Statistical and Variational Methods" by Aly A Farag|
“Biomedical Image Analysis: Statistical and Variational Methods” Book Review: This book presents the most effective modern methods in image analysis. This book covers the segmentation, registration and visualisation and algorithms. It also has the applications that have emerged from recent progress in computer vision, imaging and computational biomedical science. It has signals, systems, image formation and modality, stochastic models, computational geometry, level set methods and tools and CAD models. It also provides mathematical and statistical topics. This book theory is connected to practical examples in x-ray, ultrasound, nuclear medicine, MRI and CT imaging, removing the abstract nature of the models.
|2."Applied Medical Image Processing, Second Edition: A Basic Course" by Wolfgang Birkfellner|
“Applied Medical Image Processing, Second Edition: A Basic Course” Book Review: This book gives an ideal introduction to image processing in medicine, emphasizing the clinical relevance and special requirements of the field. It covers avoiding excessive mathematical formalisms. The book presents the principles by implementing algorithms from scratch and using simple MATLAB / Octave scripts. It covers image data and illustrations on CD-ROM or website. It provides physics of medical image processing. It also discusses image formats and data storage, intensity transforms, filtering of images and applications of the Fourier transform. This book includes three-dimensional spatial transforms, volume rendering, image registration and tomographic reconstruction.
|3."Image Processing with MATLAB: Applications in Medicine and Biology (MATLAB Examples)" by Omer Demirkaya and Musa H Asyali|
“Image Processing with MATLAB: Applications in Medicine and Biology (MATLAB Examples)” Book Review: This book describes image processing and analysis. It also provides many unique MATLAB codes and functions. This book covers the theory of probability and statistics, two-dimensional fast Fourier transform, nonlinear diffusion filtering. It also covers partial differential equation (PDE)-based image denoising techniques. It presents intensity-based image segmentation methods. It includes thresholding techniques, K-means and fuzzy C-means clustering techniques. This book has markov random field (MRF)-based image segmentation, boundary and curvature analysis methods also parametric and geometric deformable models. It has three specific applications of image processing and analysis. It includes reducing the way of solving problems. This book helps understand advanced concepts by applying algorithms in medicine and biology.
|4."Biosignal and Medical Image Processing" by John L Semmlow and Benjamin Griffel|
“Biosignal and Medical Image Processing” Book Review: This book is for undergraduate courses also for students in other disciplines. The book provides an understanding of image processing sufficient to allow intelligent application of the concepts. It includes a description of the underlying mathematical principles when needed. It covers signal and image processing concepts implemented using the MATLAB software package and several of its toolboxes. This book covers working depth and is motivated by current trends in biomedical engineering education. This book has the value for students in other disciplines that would benefit from a working knowledge of signal and image processing.
|5."ECG Signal Processing, Classification and Interpretation: A Comprehensive Framework of Computational Intelligence" by Witold Pedrycz and Adam Gacek|
“ECG Signal Processing, Classification and Interpretation: A Comprehensive Framework of Computational Intelligence” Book Review: The book has the various paradigms of computational intelligence, employed either singly or in combination. This book produces an effective structure for obtaining often vital information from ECG signals. The book is self-contained, addressing concepts, methodology, algorithms and case studies and applications. It has the structure in parts that covers the fundamental ideas of computational intelligence. The book has the principles of data acquisition, morphology and use in diagnosis. It also deals with techniques and models of computational intelligence that are suitable for signal processing. It has detailed ECG system-diagnostic interpretation and knowledge acquisition architectures. This has Illustrative material which includes brief numerical experiments, detailed schemes, exercises and more advanced problems for better understanding.
|6."Biomedical Image Analysis and Machine Learning Technologies: Applications and Techniques (Premier Reference Source)" by Eduardo Romero and Fabio A Gonzalez|
“Biomedical Image Analysis and Machine Learning Technologies: Applications and Techniques (Premier Reference Source)” Book Review: This book presents medical images at the base of many routine clinical decisions and their influence continues to increase in many fields of medicine. This book includes biomedical image analysis and machine learning technologies. It also includes applications and techniques that provide a panorama of the current boundary between biomedical complexity coming from the medical image. This innovative publication serves as a leading industry reference as well as a source of creative ideas for applications of medical issues.
|7."High-Throughput Image Reconstruction and Analysis" by Guillermo A Cecchi and A Ravishankar Rao|
“High-Throughput Image Reconstruction and Analysis” Book Review: The book is for bioinformatics or biomedical engineering graduate students. This is also useful for cell biologists, microscope manufacturers, HPC developers and drug discovery professionals. This book describes the coupling of high-performance computing (HPC). It also describes how automated imaging techniques can impact the complex biological systems. It also provides an integrated view of technology-driven capability in science. It has HPC which is used beneficially to create and analyze complex models gathered from large biological data sets. The book consists of research of respective topics with varying degrees of balance between theoretic presentation and real-world case summation and overview.
|8."Biomedical Image Segmentation: Advances and Trends" by Ayman El-Baz and Xiaoyi Jiang|
“Biomedical Image Segmentation: Advances and Trends” Book Review: This book has biomedical imaging, image segmentation provides the foundation for quantitative reasoning and diagnostic techniques. It covers a large variety of different imaging techniques. It has the physical principle and characteristics (e.g., noise modeling), often requiring modality-specific algorithmic treatment. This book has made substantial progress in biomedical image segmentation. It has biomedical image segmentation which is characterized by several specific factors. This book presents an overview of the advanced segmentation algorithms and their applications.
|9."Applied Medical Image Processing: A Basic Course" by Wolfgang Birkfellner|
“Applied Medical Image Processing: A Basic Course” Book Review: This book is a tangible and accessible presentation demonstrating real-life applications. This book is based on clinical environments and their extensive teaching experience, applied medical image processing. It has a basic course that introduces the basic methods in applied image processing beyond basic applied mathematics, physics, and programming. It is also illustrated with simple, well-commented MATLAB® examples. This book also shows the rapid evolution of radiological imaging in medical image processing into the forefront as an essential tool for clinical research. It has a crucial component of modern diagnostics and an indispensable element in the actual treatment of diseases. It covers an introduction to the basic image processing algorithms used in clinical routine applications, applied Medical Image Processing. It also covers a basic gap between basic engineering knowledge such as simple programming and applied mathematics. It also has the general understanding of a science that affects the health of a broad public.
|10."Biomedical Image Understanding: Methods and Applications (Wiley Series in Biomedical Engineering and Multi–Disciplinary Integrated Systems.)" by Sim–Heng Ong and Wei Xiong|
“Biomedical Image Understanding: Methods and Applications (Wiley Series in Biomedical Engineering and Multi–Disciplinary Integrated Systems.)” Book Review: This book presents image understanding and semantic interpretation. It covers image processing, image filtering, enhancement. It also covers de-noising, restoration and reconstruction, image segmentation and feature extraction, registration. It also includes clustering, pattern classification and data fusion. It also describes important clinical applications, virtual colonoscopy, ocular disease diagnosis and liver tumor detection. It also includes case study or applications diagrams and illustrations. This book is an essential resource for the research and applications in biomedical image understanding. This book also provides a complete set of signal and image processing tools. It includes diagnostic decision-making tools and classification methods. It has nonlinear methods for describing and classifying signals, including entropy-based methods and scaling methods.
3. Advance Medical Image Processing
|1."Guide to Medical Image Analysis: Methods and Algorithms (Advances in Computer Vision and Pattern Recognition)" by Klaus D Toennies|
“Guide to Medical Image Analysis: Methods and Algorithms (Advances in Computer Vision and Pattern Recognition)” Book Review: The book is beneficial for practitioners, computer scientists, electrical engineers and students of medical image processing and analysis. The book discusses imaging techniques, reconstruction techniques and image artifacts. It describes various techniques for image enhancement, feature detection, feature generation, segmentation, registration and validation. The book provides the use of deep convolutional networks for segmentation and labeling tasks. The book also contains information about Markov random field optimization, variational calculus and principal component analysis. Each chapter of the book contains exercise questions at the end of chapter.
|2."Advances in Low-Level Color Image Processing (Lecture Notes in Computational Vision and Biomechanics)" by M Emre Celebi and Bogdan Smolka|
“Advances in Low-Level Color Image Processing (Lecture Notes in Computational Vision and Biomechanics)” Book Review: This book describes developments in digital color imaging and computer hardware technology. It includes medical imaging, content-based image retrieval, biometrics and watermarking. The book also contains digital inpainting, remote sensing and visual quality inspection. The book introduces the color image processing pipeline.
|3."Advanced Algorithmic Approaches to Medical Image Segmentation" by S Kamaledin Setarehdan and Sameer Singh|
“Advanced Algorithmic Approaches to Medical Image Segmentation” Book Review: The book discusses medical imaging, required for diagnosis and patient care. It includes information about various imaging modalities like X-rays, computed tomography (CT), magnetic resonance imaging (MRI) and ultrasound. The book explains the model-based segmentation techniques for cardiac, brain, breast and microscopic cancer cell imaging.
|4."Advances in Computational Vision and Medical Image Processing" by R M Natal Jorge and Jo O Manuel R S Tavares|
“Advances in Computational Vision and Medical Image Processing” Book Review: The book contains developments in computational vision and medical image processing. The book tells that mathematics, statistics, psychology, mechanics and physics are used in computational vision. It describes the shape reconstruction, segmentation, registration, behaviour interpretation and simulation, motion and deformation analysis, virtual reality and tissue characterization in modeling.
|5."Medical Image Processing Concepts and Applications" by Sinha G R|
“Medical Image Processing Concepts and Applications” Book Review: The book can be referred by undergraduate and postgraduate students of biomedical engineering, computer science engineering and IT. It describes the biomedical image processing, medical image restoration, biomedical image segmentation and soft computing techniques. It presents the noise reduction filters for medical images. The book contains feature extraction and statistical measurement. The book explains the morphological operations used in medical image processing.
|6."Handbook of Medical Image Processing and Analysis (Academic Press Series in Biomedical Engineering)" by Isaac Bankman|
“Handbook of Medical Image Processing and Analysis (Academic Press Series in Biomedical Engineering)” Book Review: The book is beneficial for biomedical engineers, researchers and professionals of medical imaging and medical image processing. It describes the techniques used in processing and analyzing medical images. The book explains higher order statistics for tissue segmentation and growth modeling in oncological image analysis. It gives the analysis of cell nuclear features in fluorescence microscopy images. The book presents imaging and communication in medical and public health informatics. It also explains the dynamic mammogram retrieval from web-based image libraries.
|7."Digital Image Processing for Medical Applications South Asian Edition" by Geoff Dougherty|
“Digital Image Processing for Medical Applications South Asian Edition” Book Review: The book is useful for graduate and undergraduate students, who are interested in knowing about digital image processing. The book includes basics of major clinical imaging modalities. It gives the standard image processing operations. It uses actual medical pictures and conditions to clearly understand the concepts.
|8."Spectral and Shape Analysis in Medical Imaging: First International Workshop" by Martin Reuter and Christian Wachinger|
“Spectral and Shape Analysis in Medical Imaging: First International Workshop” Book Review: This book is written for the undergraduate students of structural engineering. It can also be used by working professionals as a reference. This book has the collection of various research papers in the field of medical imaging. The topics covered are shape and spectral analysis in medical imaging. It includes the refereed proceedings after the conference of the Workshop. It also reviews the concepts of longitudinal methods, spectral methods and shape methods. This book has included many scientific diagrams. It also has many real-life case studies to simplify the concepts.