Download or read book Robust Texture Features with Applications in Medical Imaging written by Rouzbeh Maani and published by . This book was released on 2015 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image texture is defined as visual patterns appearing in images. The powerful perceptive capability of texture features has made texture analysis a major research topic in computer vision and image processing. Texture features are used to detect defective products in factories, to understand human actions in surveillance systems, to identify people from biometric data (e.g., fingerprint, iris scan, and face photo), and to find abnormality in medical images. Indeed, many advanced applications take a direct or indirect advantage of texture analysis in their processing. An ideal texture feature should not only be discriminative but also be robust to imaging distortions. The developement of robust texture features is first motivated by applying texture analysis to Amyotrophic Lateral Sclerosis (ALS). ALS is a fatal neurodegenerative disease in which evidence of the disease is not perceptible in routine magnetic resonance images (MRI) of the brain even to a trained eye. Unlike brain tumors or multiple sclerosis, the lack of observable features possesses challenges to the detection and diagnosis of ALS. These challenges and the great need in the ALS research community to find a biomarker and to detect the patterns of degeneration in the brain have encouraged the author to study this disease using texture analysis. The results of this thesis suggest texture analysis is a potential biomarker for the disease and hence, open up new avenues towards understanding the disease. This thesis presents a useful approach for texture analysis of the brain. In contrast to the current methods, the proposed approach does not need a region of interest. It performs a voxel based texture analysis and provides a statistical map showing the regions in the brain statistically different between the groups of patients and healthy subjects. A Computer Aided Diagnosis (CAD) tool is developed for this purpose. This toolbox is called the Statistical MAp fRom Texture (SMART) and helps doctors make diagnoses and monitor the progression of diseases using texture analysis. Distortions and effects in real images (e.g., noise, illumination change, blurr effect) increase demand for developing robuts texture features. To address the robustness issues, a novel approach is presented called the Local Frequancy Descriptor (LFD). The LFD is the basis of several novel 2D and 3D texture features presented later in this thesis. It is also the basis of new image gradient operators for 2D and 3D images and a novel image matching method. All texture features, methods, and gradient operators defined based on the LFD show high accuracy and outperform the state-ofthe-art methods. In addition, they present remarkable robutness to imaging effects.
Download or read book Handbook of Texture Analysis written by Ayman El-Baz and published by CRC Press. This book was released on 2024-06-21 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: The major goals of texture research in computer vision are to understand, model, and process texture and, ultimately, to simulate the human visual learning process using computer technologies. In the last decade, artificial intelligence has been revolutionized by machine learning and big data approaches, outperforming human prediction on a wide range of problems. In particular, deep learning convolutional neural networks (CNNs) are particularly well suited to texture analysis. This volume presents important branches of texture analysis methods which find a proper application in AI-based medical image analysis. This book: Discusses first-order, second-order statistical methods, local binary pattern (LBP) methods, and filter bank-based methods Covers spatial frequency-based methods, Fourier analysis, Markov random fields, Gabor filters, and Hough transformation Describes advanced textural methods based on DL as well as BD and advanced applications of texture to medial image segmentation Is aimed at researchers, academics, and advanced students in biomedical engineering, image analysis, cognitive science, and computer science and engineering This is an essential reference for those looking to advance their understanding in this applied and emergent field.
Download or read book Handbook of Texture Analysis written by Ayman El-Baz and published by CRC Press. This book was released on 2024-06-24 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: The major goals of texture research in computer vision are to understand, model, and process texture, and ultimately, to simulate the human visual learning process using computer technologies. In the last decade, artificial intelligence has been revolutionized by machine learning and big data approaches, outperforming human prediction on a wide range of problems. In particular, deep learning convolutional neural networks (CNNs) are particularly well suited to texture analysis. This book examines four major application domains related to texture analysis and their relationship to AI-based industrial applications: texture classification, texture segmentation, shape from texture, and texture synthesis. This volume: Discusses texture-based segmentation for extracting image shape features, modeling and segmentation of noisy and textured images, spatially constrained color-texture model for image segmentation, and texture segmentation using Gabor filters Examines textural features for image classification, a statistical approach for classification, texture classification from random features, and applications of texture classifications Describes shape from texture, including general principles, 3D shapes, and equations for recovering shape from texture Surveys texture modeling, including extraction based on Hough transformation and cycle detection, image quilting, gray level run lengths, and use of Markov random fields Aimed at researchers, academics, and advanced students in biomedical engineering, image analysis, cognitive science, and computer science and engineering, this is an essential reference for those looking to advance their understanding in this applied and emergent field.
Download or read book Biomedical Texture Analysis written by Adrien Depeursinge and published by Academic Press. This book was released on 2017-08-25 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 are described and their ability to characterize BTs are demonstrated in a variety of applications in radiology and digital histopathology. Recent open-source software frameworks which enable the extraction, exploration and analysis of 2D and 3D texture-based imaging biomarkers are also presented. 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. - Defines biomedical texture precisely and describe how it is different from general texture information considered in computer vision - Defines the general problem to translate 2D and 3D texture patterns from biomedical images to visually and biologically relevant measurements - Describes, using 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 - Identifies 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 - Showcases applications where biomedical texture analysis has succeeded and failed - Provides details on existing, freely available texture analysis software, helping experts in medicine or biology develop and test precise research hypothesis
Download or read book 6th European Conference of the International Federation for Medical and Biological Engineering written by Igor Lacković and published by Springer. This book was released on 2014-09-02 with total page 1065 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents the Proceedings of the 6th European Conference of the International Federation for Medical and Biological Engineering (MBEC2014), held in Dubrovnik September 7 – 11, 2014. The general theme of MBEC 2014 is "Towards new horizons in biomedical engineering" The scientific discussions in these conference proceedings include the following themes: - Biomedical Signal Processing - Biomedical Imaging and Image Processing - Biosensors and Bioinstrumentation - Bio-Micro/Nano Technologies - Biomaterials - Biomechanics, Robotics and Minimally Invasive Surgery - Cardiovascular, Respiratory and Endocrine Systems Engineering - Neural and Rehabilitation Engineering - Molecular, Cellular and Tissue Engineering - Bioinformatics and Computational Biology - Clinical Engineering and Health Technology Assessment - Health Informatics, E-Health and Telemedicine - Biomedical Engineering Education
Download or read book Texture Feature Extraction Techniques for Image Recognition written by Jyotismita Chaki and published by Springer Nature. This book was released on 2019-10-24 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book describes various texture feature extraction approaches and texture analysis applications. It introduces and discusses the importance of texture features, and describes various types of texture features like statistical, structural, signal-processed and model-based. It also covers applications related to texture features, such as facial imaging. It is a valuable resource for machine vision researchers and practitioners in different application areas.
Download or read book Big Data in Multimodal Medical Imaging written by Ayman El-Baz and published by CRC Press. This book was released on 2019-11-05 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is an urgent need to develop and integrate new statistical, mathematical, visualization, and computational models with the ability to analyze Big Data in order to retrieve useful information to aid clinicians in accurately diagnosing and treating patients. The main focus of this book is to review and summarize state-of-the-art big data and deep learning approaches to analyze and integrate multiple data types for the creation of a decision matrix to aid clinicians in the early diagnosis and identification of high risk patients for human diseases and disorders. Leading researchers will contribute original research book chapters analyzing efforts to solve these important problems.
Download or read book Deep Learning in Medical Image Analysis written by Gobert Lee and published by Springer Nature. This book was released on 2020-02-06 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents cutting-edge research and applications of deep learning in a broad range of medical imaging scenarios, such as computer-aided diagnosis, image segmentation, tissue recognition and classification, and other areas of medical and healthcare problems. Each of its chapters covers a topic in depth, ranging from medical image synthesis and techniques for muskuloskeletal analysis to diagnostic tools for breast lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical image analysis and highlights issues and challenges encountered by researchers and clinicians, surveying and discussing practical approaches in general and in the context of specific problems. Academics, clinical and industry researchers, as well as young researchers and graduate students in medical imaging, computer-aided-diagnosis, biomedical engineering and computer vision will find this book a great reference and very useful learning resource.
Download or read book Medical Imaging written by Okechukwu Felix Erondu and published by BoD – Books on Demand. This book was released on 2011-12-22 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: What we know about and do with medical imaging has changed rapidly during the past decade, beginning with the basics, following with the breakthroughs, and moving on to the abstract. This book demonstrates the wider horizon that has become the mainstay of medical imaging sciences; capturing the concept of medical diagnosis, digital information management and research. It is an invaluable tool for radiologists and imaging specialists, physicists and researchers interested in various aspects of imaging.
Download or read book Signal Processing Image Processing and Pattern Recognition written by Tai-hoon Kim and published by Springer Science & Business Media. This book was released on 2011-11-29 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprises selected papers of the International Conference on Signal Processing, Image Processing and Pattern Recognition, SIP 2011, held as Part of the Future Generation Information Technology Conference, FGIT 2011, in Conjunction with GDC 2011, in Conjunction with GDC 2011, Jeju Island, Korea, in December 2011. The papers presented were carefully reviewed and selected from numerous submissions and focus on the various aspects of signal processing, image processing and pattern recognition.
Download or read book Medical Imaging in Clinical Applications written by Nilanjan Dey and published by Springer. This book was released on 2016-06-03 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume comprises of 21 selected chapters, including two overview chapters devoted to abdominal imaging in clinical applications supported computer aided diagnosis approaches as well as different techniques for solving the pectoral muscle extraction problem in the preprocessing part of the CAD systems for detecting breast cancer in its early stage using digital mammograms. The aim of this book is to stimulate further research in medical imaging applications based algorithmic and computer based approaches and utilize them in real-world clinical applications. The book is divided into four parts, Part-I: Clinical Applications of Medical Imaging, Part-II: Classification and clustering, Part-III: Computer Aided Diagnosis (CAD) Tools and Case Studies and Part-IV: Bio-inspiring based Computer Aided diagnosis techniques.
Download or read book Pattern Recognition and Machine Intelligence written by Bhabesh Deka and published by Springer Nature. This book was released on 2019-11-25 with total page 678 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set of LNCS 11941 and 11942 constitutes the refereed proceedings of the 8th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2019, held in Tezpur, India, in December 2019. The 131 revised full papers presented were carefully reviewed and selected from 341 submissions. They are organized in topical sections named: Pattern Recognition; Machine Learning; Deep Learning; Soft and Evolutionary Computing; Image Processing; Medical Image Processing; Bioinformatics and Biomedical Signal Processing; Information Retrieval; Remote Sensing; Signal and Video Processing; and Smart and Intelligent Sensors.
Download or read book Advances in Computer Graphics written by Bin Sheng and published by Springer Nature. This book was released on 2024-01-19 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 4-volume set of LNCS 14495-14498 constitutes the proceedings of the 40th Computer Graphics International Conference, CGI 2023, held in Shanghai, China, August 28 – September 1, 2023. The 149 papers in this set were carefully reviewed and selected from 385 submissions. They are organized in topical sections as follows: Detection and Recognition; Image Analysis and Processing; Image Restoration and Enhancement; Image Attention and Perception; Reconstruction; Rendering and Animation; Synthesis and Generation; Visual Analytics and Modeling; Graphics and AR/VR; Medical Imaging and Robotics; Theoretical Analysis; Image Analysis and Visualization in Advanced Medical Imaging Technology; Empowering Novel Geometric Algebra for Graphics and Engineering.
Download or read book Enhancing Medical Imaging with Emerging Technologies written by Sharma, Avinash Kumar and published by IGI Global. This book was released on 2024-04-15 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of medical imaging is rapidly evolving, with new technologies and techniques constantly emerging. However, this fast-paced advancement brings challenges such as the complexity of imaging modalities, the need for continuous education and training, and the integration of emerging technologies like AI and robotics into existing healthcare systems. Healthcare professionals and technology enthusiasts often need help to keep pace with these changes and may feel overwhelmed by the vast amount of information and possibilities in the field. Enhancing Medical Imaging with Emerging Technologies offers a comprehensive solution to these challenges. By providing a thorough introduction to medical imaging systems, including the fundamentals of system theory and image processing, the book serves as a foundational resource for understanding the complex world of medical imaging. It covers various imaging modalities, from conventional camera systems to advanced techniques like magnetic resonance imaging and optical coherence tomography, offering readers a holistic view of the field. This book is a valuable resource that inspires hope, sparks curiosity, and paints a vivid picture of the limitless potential of medical imaging.
Download or read book The Application of Radiomics and Artificial Intelligence in Cancer Imaging written by Jiuquan Zhang and published by Frontiers Media SA. This book was released on 2022-03-21 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Content Based Image Classification written by Rik Das and published by CRC Press. This book was released on 2020-12-17 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: Content-Based Image Classification: Efficient Machine Learning Using Robust Feature Extraction Techniques is a comprehensive guide to research with invaluable image data. Social Science Research Network has revealed that 65% of people are visual learners. Research data provided by Hyerle (2000) has clearly shown 90% of information in the human brain is visual. Thus, it is no wonder that visual information processing in the brain is 60,000 times faster than text-based information (3M Corporation, 2001). Recently, we have witnessed a significant surge in conversing with images due to the popularity of social networking platforms. The other reason for embracing usage of image data is the mass availability of high-resolution cellphone cameras. Wide usage of image data in diversified application areas including medical science, media, sports, remote sensing, and so on, has spurred the need for further research in optimizing archival, maintenance, and retrieval of appropriate image content to leverage data-driven decision-making. This book demonstrates several techniques of image processing to represent image data in a desired format for information identification. It discusses the application of machine learning and deep learning for identifying and categorizing appropriate image data helpful in designing automated decision support systems. The book offers comprehensive coverage of the most essential topics, including: Image feature extraction with novel handcrafted techniques (traditional feature extraction) Image feature extraction with automated techniques (representation learning with CNNs) Significance of fusion-based approaches in enhancing classification accuracy MATLAB® codes for implementing the techniques Use of the Open Access data mining tool WEKA for multiple tasks The book is intended for budding researchers, technocrats, engineering students, and machine learning/deep learning enthusiasts who are willing to start their computer vision journey with content-based image recognition. The readers will get a clear picture of the essentials for transforming the image data into valuable means for insight generation. Readers will learn coding techniques necessary to propose novel mechanisms and disruptive approaches. The WEKA guide provided is beneficial for those uncomfortable coding for machine learning algorithms. The WEKA tool assists the learner in implementing machine learning algorithms with the click of a button. Thus, this book will be a stepping-stone for your machine learning journey. Please visit the author's website for any further guidance at https://www.rikdas.com/
Download or read book Innovation in Medicine and Healthcare 2015 written by Yen-Wei Chen and published by Springer. This book was released on 2015-08-31 with total page 587 pages. Available in PDF, EPUB and Kindle. Book excerpt: Innovation in medicine and healthcare is an interdisciplinary research area, which combines the advanced technologies and problem solving skills with medical and biological science. A central theme of this proceedings is Smart Medical and Healthcare Systems (modern intelligent systems for medicine and healthcare), which can provide efficient and accurate solution to problems faced by healthcare and medical practitioners today by using advanced information communication techniques, computational intelligence, mathematics, robotics and other advanced technologies. The techniques developed in this area will have a significant effect on future medicine and healthcare. The volume includes 53 papers, which present the recent trend and innovations in medicine and healthcare including Medical Informatics; Biomedical Engineering; Management for Healthcare; Advanced ICT for Medical and Healthcare; Simulation and Visualization/VR for Medicine; Statistical Signal Processing and Artificial Intelligence; Smart Medical and Healthcare System and Healthcare Support System.
