Advanced Machine Vision Paradigms for Medical Image Analysis

Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis

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  • Author : Tapan K. Gandhi
  • Publisher : Academic Press
  • Pages : 308 pages
  • ISBN : 0128192968
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKAdvanced Machine Vision Paradigms for Medical Image Analysis

Advanced Machine Vision Paradigms for Medical Image Analysis

Advanced Machine Vision Paradigms for Medical Image Analysis
  • Author : Tapan K. Gandhi,Siddhartha Bhattacharyya,Sourav De,Debanjan Konar,Sandip Dey
  • Publisher : Academic Press
  • Release : 11 August 2020
GET THIS BOOKAdvanced Machine Vision Paradigms for Medical Image Analysis

Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured

Computer Vision and Machine Intelligence in Medical Image Analysis

Computer Vision and Machine Intelligence in Medical Image Analysis
  • Author : Mousumi Gupta,Debanjan Konar,Siddhartha Bhattacharyya,Sambhunath Biswas
  • Publisher : Springer Nature
  • Release : 28 August 2019
GET THIS BOOKComputer Vision and Machine Intelligence in Medical Image Analysis

This book includes high-quality papers presented at the Symposium 2019, organised by Sikkim Manipal Institute of Technology (SMIT), in Sikkim from 26–27 February 2019. It discusses common research problems and challenges in medical image analysis, such as deep learning methods. It also discusses how these theories can be applied to a broad range of application areas, including lung and chest x-ray, breast CAD, microscopy and pathology. The studies included mainly focus on the detection of events from biomedical signals.

Hybrid Machine Intelligence for Medical Image Analysis

Hybrid Machine Intelligence for Medical Image Analysis
  • Author : Siddhartha Bhattacharyya,Debanjan Konar,Jan Platos,Chinmoy Kar,Kalpana Sharma
  • Publisher : Springer
  • Release : 08 August 2019
GET THIS BOOKHybrid Machine Intelligence for Medical Image Analysis

The book discusses the impact of machine learning and computational intelligent algorithms on medical image data processing, and introduces the latest trends in machine learning technologies and computational intelligence for intelligent medical image analysis. The topics covered include automated region of interest detection of magnetic resonance images based on center of gravity; brain tumor detection through low-level features detection; automatic MRI image segmentation for brain tumor detection using the multi-level sigmoid activation function; and computer-aided detection of mammographic lesions using

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

Medical Image Recognition, Segmentation and Parsing

Medical Image Recognition, Segmentation and Parsing
  • Author : S. Kevin Zhou
  • Publisher : Academic Press
  • Release : 11 December 2015
GET THIS BOOKMedical Image Recognition, Segmentation and Parsing

This book describes the technical problems and solutions for automatically recognizing and parsing a medical image into multiple objects, structures, or anatomies. It gives all the key methods, including state-of- the-art approaches based on machine learning, for recognizing or detecting, parsing or segmenting, a cohort of anatomical structures from a medical image. Written by top experts in Medical Imaging, this book is ideal for university researchers and industry practitioners in medical imaging who want a complete reference on key methods,

Natural User Interfaces in Medical Image Analysis

Natural User Interfaces in Medical Image Analysis
  • Author : Marek R. Ogiela,Tomasz Hachaj
  • Publisher : Springer
  • Release : 07 June 2014
GET THIS BOOKNatural User Interfaces in Medical Image Analysis

This unique text/reference highlights a selection of practical applications of advanced image analysis methods for medical images. The book covers the complete methodology for processing, analysing and interpreting diagnostic results of sample CT images. The text also presents significant problems related to new approaches and paradigms in image understanding and semantic image analysis. To further engage the reader, example source code is provided for the implemented algorithms in the described solutions. Features: describes the most important methods and algorithms

Soft Computing Based Medical Image Analysis

Soft Computing Based Medical Image Analysis
  • Author : Nilanjan Dey,Amira Ashour,Fuquian Shi,Valentina E. Balas
  • Publisher : Academic Press
  • Release : 18 January 2018
GET THIS BOOKSoft Computing Based Medical Image Analysis

Soft Computing Based Medical Image Analysis presents the foremost techniques of soft computing in medical image analysis and processing. It includes image enhancement, segmentation, classification-based soft computing, and their application in diagnostic imaging, as well as an extensive background for the development of intelligent systems based on soft computing used in medical image analysis and processing. The book introduces the theory and concepts of digital image analysis and processing based on soft computing with real-world medical imaging applications. Comparative studies

Computer Vision in Advanced Control Systems-5

Computer Vision in Advanced Control Systems-5
  • Author : Margarita N. Favorskaya,Lakhmi C. Jain
  • Publisher : Springer Nature
  • Release : 07 December 2019
GET THIS BOOKComputer Vision in Advanced Control Systems-5

This book applies novel theories to improve algorithms in complex data analysis in various fields, including object detection, remote sensing, data transmission, data fusion, gesture recognition, and medical image processing and analysis. It is intended for Ph.D. students, academics, researchers, and software developers working in the areas of digital video processing and computer vision technologies.

Advanced Computational Intelligence Paradigms in Healthcare - 3

Advanced Computational Intelligence Paradigms in Healthcare - 3
  • Author : Margarita Sordo,Sachin Vaidya
  • Publisher : Springer
  • Release : 20 August 2008
GET THIS BOOKAdvanced Computational Intelligence Paradigms in Healthcare - 3

This volume details the latest state-of-the-art research on computational intelligence paradigms in healthcare in the intelligent agent environment. The book presents seven chapters selected from the rapidly growing application areas of computational intelligence to healthcare systems. These include intelligent synthetic characters, man-machine interface, menu generators, analysis of user acceptance, pictures archiving and communication systems.

Decision Forests for Computer Vision and Medical Image Analysis

Decision Forests for Computer Vision and Medical Image Analysis
  • Author : Antonio Criminisi,J Shotton
  • Publisher : Springer Science & Business Media
  • Release : 30 January 2013
GET THIS BOOKDecision Forests for Computer Vision and Medical Image Analysis

This practical and easy-to-follow text explores the theoretical underpinnings of decision forests, organizing the vast existing literature on the field within a new, general-purpose forest model. Topics and features: with a foreword by Prof. Y. Amit and Prof. D. Geman, recounting their participation in the development of decision forests; introduces a flexible decision forest model, capable of addressing a large and diverse set of image and video analysis tasks; investigates both the theoretical foundations and the practical implementation of decision

Intelligent Paradigms for Healthcare Enterprises

Intelligent Paradigms for Healthcare Enterprises
  • Author : Barry G. Silverman,Lakhmi C. Jain,Ashlesha Jain,Ajita Ichalkaranje
  • Publisher : Springer Science & Business Media
  • Release : 25 August 2005
GET THIS BOOKIntelligent Paradigms for Healthcare Enterprises

This compendium brings together leading researchers in the fields of Intelligent Systems and healthcare aiming at medical engineers, healthcare managers and computer scientists worldwide. This book is an overview of intelligent paradigms and strategic investments that might payoff for the healthcare enterprise. Specifically, the reader will get ideas for efficiency enhancements for improving effectiveness and quality of care and for increasing patient safety. "Advanced Intelligent Paradigms in Healthcare" straddles technologic topics from DNA processing and automating medical second opinions in

Algorithms for Image Processing and Computer Vision

Algorithms for Image Processing and Computer Vision
  • Author : J. R. Parker
  • Publisher : John Wiley & Sons
  • Release : 29 November 2010
GET THIS BOOKAlgorithms for Image Processing and Computer Vision

A cookbook of algorithms for common image processing applications Thanks to advances in computer hardware and software, algorithms have been developed that support sophisticated image processing without requiring an extensive background in mathematics. This bestselling book has been fully updated with the newest of these, including 2D vision methods in content-based searches and the use of graphics cards as image processing computational aids. It’s an ideal reference for software engineers and developers, advanced programmers, graphics programmers, scientists, and other

Machine Learning Paradigms

Machine Learning Paradigms
  • Author : George A. Tsihrintzis,Lakhmi C. Jain
  • Publisher : Springer Nature
  • Release : 23 July 2020
GET THIS BOOKMachine Learning Paradigms

At the dawn of the 4th Industrial Revolution, the field of Deep Learning (a sub-field of Artificial Intelligence and Machine Learning) is growing continuously and rapidly, developing both theoretically and towards applications in increasingly many and diverse other disciplines. The book at hand aims at exposing its reader to some of the most significant recent advances in deep learning-based technological applications and consists of an editorial note and an additional fifteen (15) chapters. All chapters in the book were invited from

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