Biomedical Texture Analysis

Computerized recognition and quantification of texture information has been an active research domain for the past 50 years, with some of the pioneering work still widely used today. Recently, the increasing ubiquity of imaging data has driven the need for powerful image analysis approaches to convert this data into knowledge. One of the most promising application domains is biomedical imaging, which is a key enabling technology for precision medicine (e.g., radiomics and digital histopathology) and biomedical discovery (e.g., microscopy). The colossal research efforts and progress made in the general domain of computer vision have led to extremely powerful data analysis systems. Biomedical imaging relies upon well-defined acquisition protocols to produce images. This is quite different from general photography. Consequently, the analysis of biomedical images requires a paradigm change to account for the quantitative nature of the imaging process. Texture analysis is a broadly applicable, powerful technology for quantitative analysis of biomedical images. This book provides a thorough background on texture analysis for graduate students, and biomedical engineers from both industry and academia who have basic image processing knowledge. Medical doctors and biologists with no background in image processing will also find available methods and software tools for analyzing textures in medical images. By bringing together experts in data science, medicine, and biology, we hope that this book will actively promote the translation of incredibly powerful data analysis methods into several breakthroughs in biomedical discovery and noninvasive precision medicine. Define biomedical texture precisely and describe how it is different from general texture information considered in computer vision Define the general problem to translate 2D and 3D texture patterns from biomedical images to visually and biologically relevant measurements Describe with intuitive concepts how the most popular biomedical texture analysis approaches (e.g., gray-level matrices, fractals, wavelets, deep convolutional neural networks) work, what they have in common, and how they are different Identify the strengths, weaknesses, and current challenges of existing methods including both handcrafted and learned representations, as well as deep learning. The goal is to establish foundations for building the next generation of biomedical texture operators Showcase applications where biomedical texture analysis has succeeded and failed Provide details on existing, freely available texture analysis software. This will help experts in medicine or biology develop and test precise research hypothesis

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  • Author : Adrien Depeursinge
  • Publisher : Academic Press
  • Pages : 428 pages
  • ISBN : 9780128121337
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKBiomedical Texture Analysis

Biomedical Texture Analysis

Biomedical Texture Analysis
  • Author : Adrien Depeursinge,Omar Al-Kadi,J. Ross Mitchell
  • Publisher : Academic Press
  • Release : 01 August 2017
GET THIS BOOKBiomedical Texture Analysis

Computerized recognition and quantification of texture information has been an active research domain for the past 50 years, with some of the pioneering work still widely used today. Recently, the increasing ubiquity of imaging data has driven the need for powerful image analysis approaches to convert this data into knowledge. One of the most promising application domains is biomedical imaging, which is a key enabling technology for precision medicine (e.g., radiomics and digital histopathology) and biomedical discovery (e.g., microscopy).

Biomedical Texture Analysis

Biomedical Texture Analysis
  • Author : Adrien Depeursinge,Omar S Al-Kadi,J.Ross Mitchell
  • Publisher : Academic Press
  • Release : 25 August 2017
GET THIS BOOKBiomedical Texture Analysis

Biomedical Texture Analysis: Fundamentals, Applications, Tools and Challenges describes the fundamentals and applications of biomedical texture analysis (BTA) for precision medicine. It defines what biomedical textures (BTs) are and why they require specific image analysis design approaches when compared to more classical computer vision applications. The fundamental properties of BTs are given to highlight key aspects of texture operator design, providing a foundation for biomedical engineers to build the next generation of biomedical texture operators. Examples of novel texture operators

Advanced Biomedical Image Analysis

Advanced Biomedical Image Analysis
  • Author : Mark Haidekker
  • Publisher : John Wiley & Sons
  • Release : 29 March 2011
GET THIS BOOKAdvanced Biomedical Image Analysis

A comprehensive reference of cutting-edge advanced techniques for quantitative image processing and analysis Medical diagnostics and intervention, and biomedical research rely progressively on imaging techniques, namely, the ability to capture, store, analyze, and display images at the organ, tissue, cellular, and molecular level. These tasks are supported by increasingly powerful computer methods to process and analyze images. This text serves as an authoritative resource and self-study guide explaining sophisticated techniques of quantitative image analysis, with a focus on biomedical applications.

Advances in Computational Techniques for Biomedical Image Analysis

Advances in Computational Techniques for Biomedical Image Analysis
  • Author : Deepika Koundal,Savita Gupta
  • Publisher : Academic Press
  • Release : 28 May 2020
GET THIS BOOKAdvances in Computational Techniques for Biomedical Image Analysis

Advances in Computational Techniques for Biomedical Image Analysis: Methods and Applications focuses on post-acquisition challenges such as image enhancement, detection of edges and objects, analysis of shape, quantification of texture and sharpness, and pattern analysis. It discusses the archiving and transfer of images, presents a selection of techniques for the enhancement of contrast and edges, for noise reduction and for edge-preserving smoothing. It examines various feature detection and segmentation techniques, together with methods for computing a registration or normalization transformation.

Biomedical Image Analysis

Biomedical Image Analysis
  • Author : Rangaraj M. Rangayyan
  • Publisher : CRC Press
  • Release : 30 December 2004
GET THIS BOOKBiomedical Image Analysis

Computers have become an integral part of medical imaging systems and are used for everything from data acquisition and image generation to image display and analysis. As the scope and complexity of imaging technology steadily increase, more advanced techniques are required to solve the emerging challenges. Biomedical Image Analysis demonstr

Biomedical Image Processing

Biomedical Image Processing
  • Author : Thomas Martin Deserno
  • Publisher : Springer Science & Business Media
  • Release : 01 March 2011
GET THIS BOOKBiomedical Image Processing

In modern medicine, imaging is the most effective tool for diagnostics, treatment planning and therapy. Almost all modalities have went to directly digital acquisition techniques and processing of this image data have become an important option for health care in future. This book is written by a team of internationally recognized experts from all over the world. It provides a brief but complete overview on medical image processing and analysis highlighting recent advances that have been made in academics. Color

Assessment of Cellular and Organ Function and Dysfunction using Direct and Derived MRI Methodologies

Assessment of Cellular and Organ Function and Dysfunction using Direct and Derived MRI Methodologies
  • Author : Christakis Constantinides
  • Publisher : BoD – Books on Demand
  • Release : 26 October 2016
GET THIS BOOKAssessment of Cellular and Organ Function and Dysfunction using Direct and Derived MRI Methodologies

Despite the tremendous growth in the field of magnetic resonance imaging (MRI) evidenced in the initial phases of its development in the early twentieth century, scientific focus has shifted in recent years toward the study of physiology and pathophysiology that span the spatial scales of the molecule, cell, tissue, and organ. Intensified research activities over the past 15 years have justified efforts toward molecular and cellular imaging, dual-modality imaging systems, real-time acquisitions, dedicated image processing techniques and applications, and the critical

Interpretable and Annotation-Efficient Learning for Medical Image Computing

Interpretable and Annotation-Efficient Learning for Medical Image Computing
  • Author : Jaime Cardoso,Hien Van Nguyen,Nicholas Heller,Pedro Henriques Abreu,Ivana Isgum,Wilson Silva,Ricardo Cruz,Jose Pereira Amorim,Vishal Patel,Badri Roysam,Kevin Zhou,Steve Jiang,Ngan Le,Khoa Luu,Raphael Sznitman,Veronika Cheplygina,Diana Mateus,Emanuele Trucco,Samaneh Abbasi
  • Publisher : Springer Nature
  • Release : 03 October 2020
GET THIS BOOKInterpretable and Annotation-Efficient Learning for Medical Image Computing

This book constitutes the refereed joint proceedings of the Third International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2020, the Second International Workshop on Medical Image Learning with Less Labels and Imperfect Data, MIL3ID 2020, and the 5th International Workshop on Large-scale Annotation of Biomedical data and Expert Label Synthesis, LABELS 2020, held in conjunction with the 23rd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020. The 8 full papers presented at iMIMIC 2020, 11

Computers in Medical Activity

Computers in Medical Activity
  • Author : Edward Kacki,Marek Rudnicki,Joanna Stempczynska
  • Publisher : Springer Science & Business Media
  • Release : 13 October 2009
GET THIS BOOKComputers in Medical Activity

Papers selected to the present monograph are only a small piece of subjects being investigated in Poland in the range of medical computer science. Their summaries and preliminary results were presented during the international conference „Computers in Medical Activity" organized by the College of Computer Science in Lodz with the collaboration of the Polish Society of Medical Computer Science in Poland in 2007. The subject matter of the monograph is mainly steered on employing the computer systems in the diagnostics then

Riemannian Geometric Statistics in Medical Image Analysis

Riemannian Geometric Statistics in Medical Image Analysis
  • Author : Xavier Pennec,Stefan Sommer,Tom Fletcher
  • Publisher : Academic Press
  • Release : 01 September 2019
GET THIS BOOKRiemannian Geometric Statistics in Medical Image Analysis

Over the past 15 years, there has been a growing need in the medical image computing community for principled methods to process nonlinear geometric data. Riemannian geometry has emerged as one of the most powerful mathematical and computational frameworks for analyzing such data. Riemannian Geometric Statistics in Medical Image Analysis is a complete reference on statistics on Riemannian manifolds and more general nonlinear spaces with applications in medical image analysis. It provides an introduction to the core methodology followed by a

Image Processing

Image Processing
  • Author : Yung-Sheng Chen
  • Publisher : BoD – Books on Demand
  • Release : 01 December 2009
GET THIS BOOKImage Processing

There are six sections in this book. The first section presents basic image processing techniques, such as image acquisition, storage, retrieval, transformation, filtering, and parallel computing. Then, some applications, such as road sign recognition, air quality monitoring, remote sensed image analysis, and diagnosis of industrial parts are considered. Subsequently, the application of image processing for the special eye examination and a newly three-dimensional digital camera are introduced. On the other hand, the section of medical imaging will show the applications

Biomedical Diagnostics and Clinical Technologies: Applying High-Performance Cluster and Grid Computing

Biomedical Diagnostics and Clinical Technologies: Applying High-Performance Cluster and Grid Computing
  • Author : Pereira, Manuela,Freire, Mario
  • Publisher : IGI Global
  • Release : 30 September 2010
GET THIS BOOKBiomedical Diagnostics and Clinical Technologies: Applying High-Performance Cluster and Grid Computing

Biomedical Diagnostics and Clinical Technologies: Applying High-Performance Cluster and Grid Computing disseminates knowledge regarding high performance computing for medical applications and bioinformatics. This critical reference source contains a valuable collection of cutting-edge research chapters for those working in the broad field of medical informatics and bioinformatics.

Deep Learning and Parallel Computing Environment for Bioengineering Systems

Deep Learning and Parallel Computing Environment for Bioengineering Systems
  • Author : Dr. Arun Kumar Sangaiah
  • Publisher : Academic Press
  • Release : 26 July 2019
GET THIS BOOKDeep Learning and Parallel Computing Environment for Bioengineering Systems

Deep Learning and Parallel Computing Environment for Bioengineering Systems delivers a significant forum for the technical advancement of deep learning in parallel computing environment across bio-engineering diversified domains and its applications. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources. Managing the gathered knowledge and applying it to multiple domains including health care, social networks, mining, recommendation systems, image processing, pattern recognition and predictions using deep learning paradigms is the major

Bioinformatics and Biomedical Engineering

Bioinformatics and Biomedical Engineering
  • Author : Ignacio Rojas,Francisco Ortuño
  • Publisher : Springer
  • Release : 19 April 2018
GET THIS BOOKBioinformatics and Biomedical Engineering

This two volume set LNBI 10813 and LNBI 10814 constitutes the proceedings of the 6th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2018, held in Granada, Spain, in April 2018.The 88 regular papers presented were carefully reviewed and selected from 273 submissions. The scope of the conference spans the following areas: bioinformatics for healthcare and diseases; bioinformatics tools to integrate omics dataset and address biological question; challenges and advances in measurement and self-parametrization of complex biological systems; computational genomics; computational proteomics; computational systems for

Pattern Recognition and Signal Analysis in Medical Imaging

Pattern Recognition and Signal Analysis in Medical Imaging
  • Author : Anke Meyer-Baese,Volker J. Schmid
  • Publisher : Elsevier
  • Release : 21 March 2014
GET THIS BOOKPattern Recognition and Signal Analysis in Medical Imaging

Medical imaging is one of the heaviest funded biomedical engineering research areas. The second edition of Pattern Recognition and Signal Analysis in Medical Imaging brings sharp focus to the development of integrated systems for use in the clinical sector, enabling both imaging and the automatic assessment of the resultant data. Since the first edition, there has been tremendous development of new, powerful technologies for detecting, storing, transmitting, analyzing, and displaying medical images. Computer-aided analytical techniques, coupled with a continuing need