Download or read book Automated Brain Lesion Detection and Segmentation Using MR Images written by Nabizadeh Nooshin and published by LAP Lambert Academic Publishing. This book was released on 2015-07-27 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision and machine learning allows the image data to be seen by a computer or machine as a person would see it. This is a complex concept for a computer to comprehend since computers do not understand the three-dimensional perspective as a person views and understands it. Computer vision has variety of applications in industry, medicine, surveillance systems, video analysis, robotic, and etc. Image segmentation is one of the most challenging topics in computer vision and machine learning. As an application of image segmentation in biomedical research is to localize some specific cells and tissues, e.g., tumor or stroke in magnetic resonance images (MRI). Medical image segmentation helps physicians to find these lesions more accurately, and it can be great source of information in emergency cases that specialist is not available. Therefore, it is an important process in computerized medical imaging. Automated segmentation of brain lesions in MRI is a difficult procedure due to the variability and complexity of the location, size, shape, and texture of these lesions. This study presents four algorithms for brain lesion detection and segmentation using MR images.
Download or read book Automated Brain Lesion Detection and Segmentation Using Magnetic Resonance Images written by Nooshin Nabizadeh and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Automated segmentation of brain lesions in magnetic resonance images (MRI) is a difficult procedure due to the variability and complexity of the location, size, shape, and texture of these lesions. In this study, four algorithms for brain lesion detection and segmentation using MRI are proposed. In the first algorithm, an automatic algorithm for brain stroke lesion detection and segmentation using single-spectral MRI is proposed, which is called histogram-based gravitational optimization algorithm (HGOA). HGOA is a novel intensity-based segmentation technique that applies enhanced gravitational optimization algorithm on histogram analysis results to segment the brain lesion. The ischemic stroke lesions are segmented with 91.5% accuracy and tumor lesions are segmented with 88% accuracy. Since histogram analysis limits the extracted information to the number of pixels in specific gray levels and does not include any region-based information, the accuracy of a histogram-based method is limited. In the second algorithm, in order to increase the accuracy of brain tumor segmentation, a texture-based automated approach is presented. The experimental results on T1-weighted, T2-weighted, and fluid-attenuated inversion recovery (FLAIR) images on both simulated and real brain MRI data prove the efficacy of our technique in successfully segmentation of brain tumor tissues with high accuracy (95.9 ± 0.4% for database of simulated MR images, and 93.2 ± 0.3% for database of real MR images). In order to reduce the computational complexity and expedite the segmentation algorithm, and also to improve the system performance, some modifications are applied in the algorithm presented in previous algorithm. In the third algorithm, a fully automatic tumor system, which is combination of texture-based and contour-based algorithms is presented. Skippy greedy snake algorithm is capable of segmenting the tumor area; however, the algorithm's accuracy and performance depends significantly on its initial points. Here, we modify the previous algorithm to automatically find proper initial points, which not only obviates the requirement of manual interference, but also increase the accuracy and speed of optimization convergence. Comparing with previous method, this method achieves higher accuracy in tumor segmentation (96.8 ± 0.3% for database of simulated MR images, and 93.8 ± 0.1% for database of real MR images) and lower computational complexity. The intensity similarities between brain lesions and some normal tissues result in confusion within segmentation algorithms, especially in the database of real MR images. In order to improve the system performance for this database, a multi-spectral approach based on feature-level fusion is presented in forth algorithm. Even though using multi-spectral MRI has several drawbacks and limitations, since it makes use of complementary information, it increases the accuracy of the system. Here, a feature-level fusion technique based on canonical correlation analysis (CCA) is proposed. It is worth mentioning that for the first time CCA is applied for combining MRI sequences in order to segment tumors. Even though data fusion increases computational complexity of the segmentation algorithm, it results in a higher accuracy (95.8 ± 0.2% for database of real MR images).
Download or read book Brain Tumor MRI Image Segmentation Using Deep Learning Techniques written by Jyotismita Chaki and published by Academic Press. This book was released on 2021-11-27 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain Tumor MRI Image Segmentation Using Deep Learning Techniques offers a description of deep learning approaches used for the segmentation of brain tumors. The book demonstrates core concepts of deep learning algorithms by using diagrams, data tables and examples to illustrate brain tumor segmentation. After introducing basic concepts of deep learning-based brain tumor segmentation, sections cover techniques for modeling, segmentation and properties. A focus is placed on the application of different types of convolutional neural networks, like single path, multi path, fully convolutional network, cascade convolutional neural networks, Long Short-Term Memory - Recurrent Neural Network and Gated Recurrent Units, and more. The book also highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in brain tumor segmentation. Provides readers with an understanding of deep learning-based approaches in the field of brain tumor segmentation, including preprocessing techniques Integrates recent advancements in the field, including the transformation of low-resolution brain tumor images into super-resolution images using deep learning-based methods, single path Convolutional Neural Network based brain tumor segmentation, and much more Includes coverage of Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN), Gated Recurrent Units (GRU) based Recurrent Neural Network (RNN), Generative Adversarial Networks (GAN), Auto Encoder based brain tumor segmentation, and Ensemble deep learning Model based brain tumor segmentation Covers research Issues and the future of deep learning-based brain tumor segmentation
Download or read book CMBEBIH 2017 written by Almir Badnjevic and published by Springer. This book was released on 2017-03-14 with total page 806 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents the proceedings of the International Conference on Medical and Biological Engineering held from 16 to 18 March 2017 in Sarajevo, Bosnia and Herzegovina. Focusing on the theme of ‘Pursuing innovation. Shaping the future’, it highlights the latest advancements in Biomedical Engineering and also presents the latest findings, innovative solutions and emerging challenges in this field. Topics include: - 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 - Pharmaceutical Engineering
Download or read book Deep Learning and Data Labeling for Medical Applications written by Gustavo Carneiro and published by Springer. This book was released on 2016-10-07 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of two workshops held at the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, in Athens, Greece, in October 2016: the First Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2016, and the Second International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2016. The 28 revised regular papers presented in this book were carefully reviewed and selected from a total of 52 submissions. The 7 papers selected for LABELS deal with topics from the following fields: crowd-sourcing methods; active learning; transfer learning; semi-supervised learning; and modeling of label uncertainty.The 21 papers selected for DLMIA span a wide range of topics such as image description; medical imaging-based diagnosis; medical signal-based diagnosis; medical image reconstruction and model selection using deep learning techniques; meta-heuristic techniques for fine-tuning parameter in deep learning-based architectures; and applications based on deep learning techniques.
Download or read book Medical Image Computing and Computer Assisted Intervention MICCAI 2015 written by Nassir Navab and published by Springer. This book was released on 2015-09-28 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 9349, 9350, and 9351 constitutes the refereed proceedings of the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015, held in Munich, Germany, in October 2015. Based on rigorous peer reviews, the program committee carefully selected 263 revised papers from 810 submissions for presentation in three volumes. The papers have been organized in the following topical sections: quantitative image analysis I: segmentation and measurement; computer-aided diagnosis: machine learning; computer-aided diagnosis: automation; quantitative image analysis II: classification, detection, features, and morphology; advanced MRI: diffusion, fMRI, DCE; quantitative image analysis III: motion, deformation, development and degeneration; quantitative image analysis IV: microscopy, fluorescence and histological imagery; registration: method and advanced applications; reconstruction, image formation, advanced acquisition - computational imaging; modelling and simulation for diagnosis and interventional planning; computer-assisted and image-guided interventions.
Download or read book Automatic methods for multiple sclerosis new lesions detection and segmentation written by Olivier Commowick and published by Frontiers Media SA. This book was released on 2023-04-11 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Brain Lesion Detection and Tumor Segmentation in MRI Using 3D Fully Convolutional Networks written by Andrew Jesson and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "This thesis presents a generalized framework for the detection of lesions and segmentation of tumors in brain magnetic resonance imaging (MRI) using fully convolutional neural networks (FCNs). The FCN framework is chosen due to its capacity to model multi-resolution context in the image domain and yield consistent semantic segmentation results. This thesis extends the FCN framework to better suit the task of brain lesion segmentation and detection by including 3D convolutions to capture the full context of MRI volumes, a curriculum on the label weights to handle class imbalance, and a multi-scale loss to promote the modelling of context in the label domain. The proposed method is evaluated on two distinct tasks: multiple sclerosis (MS) lesion detection, and brain tumor segmentation. It is shown that this method performs at a high level for both tasks even though no fundamental changes to architecture, objective function, or optimization strategy are made. For the task of MS lesion detection, the trained model achieves a true positive rate of 0.82 at a false detection rate of 0.23 on an independent test set. The method was also submitted to the 2017 MICCAI Brain Tumor Segmentation (BraTS) Challenge, where it placed in the top five out of nearly one-hundred entrants, achieving independently evaluated dices scores of 0.860 and 0.783 for segmenting tumor and tumor core on unseen test data." --
Download or read book Intramedullary Spinal Cord Tumors written by Georges Fischer and published by Thieme. This book was released on 1996 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here is the first book in 30 years to cover all diagnostic and therapeutic aspects of intramedullary spinal cord tumors (IMTs), a relatively rare but often misdiagnosed type of tumor. You will benefit from the largest personal collection of operated cases (171) ever assembled, as well as a review of 1,100 additional cases, making this the single most comprehensive book on IMTs available today. You will also appreciate the vital role of MRI in accurately diagnosing these tumors and review the latest technical refinements in surgical methods. Divided into three parts, the book begins with the diagnostic and therapeutic problems common to all intramedullary spinal cord tumors, then covers the histology of individual tumors, and finally examines the controversial value of radiotherapy in the treatment of both benign and malignant tumors in children and adults. Throughout, full-color illustrations depict anatomy from a surgical point of view.
Download or read book Brainlesion Glioma Multiple Sclerosis Stroke and Traumatic Brain Injuries written by Alessandro Crimi and published by Springer. This book was released on 2018-02-16 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes revised selected papers from the Third International MICCAI Brainlesion Workshop, BrainLes 2017, as well as the International Multimodal Brain Tumor Segmentation, BraTS, and White Matter Hyperintensities, WMH, segmentation challenges, which were held jointly at the Medical Image computing for Computer Assisted Intervention Conference, MICCAI, in Quebec City, Canada, in September 2017. The 40 papers presented in this volume were carefully reviewed and selected from 46 submissions. They were organized in topical sections named: brain lesion image analysis; brain tumor image segmentation; and ischemic stroke lesion image segmentation.
Download or read book Brain Mri Segmentation Using Texture Features written by Anuradha Phadke and published by LAP Lambert Academic Publishing. This book was released on 2012-08 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main aim of this book is to introduce to a system which can detect brain tumor using brain Magnetic Resonance Image segmentation. Automated MRI (Magnetic Resonance Imaging) brain tumor segmentation is a difficult task due to the variance and complexity of tumors. In this work, a statistical structure analysis based brain tissue segmentation scheme is presented, which focuses on the structural analysis on both abnormal and normal tissues. As the local textures in the images can reveal the typical 'regularities' of biological structures, textural features have been extracted using co-occurrence matrix approach. By the analysis of level of correlation the number of features can be reduced to the significant components. Feed forward back propagation neural network is used for classification. Proposed techniques of analysis and classification are used to investigate the differences of texture features among macroscopic lesion white matter (LWM) and normal appearing white matter (NAWM) in magnetic resonance images (MRI) from patients with normal and abnormal white matter.
Download or read book Automated Brain Lesion Segmentation in Magnetic Resonance Images written by Simon Andermatt and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Brainlesion Glioma Multiple Sclerosis Stroke and Traumatic Brain Injuries written by Alessandro Crimi and published by Springer. This book was released on 2017-04-11 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Brain Lesion, as well as the challenges on Brain Tumor Segmentation (BRATS), Ischemic Stroke Lesion Image Segmentation (ISLES), and the Mild Traumatic Brain Injury Outcome Prediction (mTOP), held in Athens, October 17, 2016, in conjunction with the International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016. The 26 papers presented in this volume were carefully reviewed. They present the latest advances in segmentation, disease prognosis and other applications to the clinical context.
Download or read book ICT Innovations 2014 written by Ana Madevska Bogdanova and published by Springer. This book was released on 2014-08-09 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data is a common ground, a starting point for each ICT system. Data needs processing, use of different technologies and state-of-the-art methods in order to obtain new knowledge, to develop new useful applications that not only ease, but also increase the quality of life. These applications use the exploration of Big Data, High throughput data, Data Warehouse, Data Mining, Bioinformatics, Robotics, with data coming from social media, sensors, scientific applications, surveillance, video and image archives, internet texts and documents, internet search indexing, medical records, business transactions, web logs, etc. Information and communication technologies have become the asset in everyday life enabling increased level of communication, processing and information exchange. This book offers a collection of selected papers presented at the Sixth International Conference on ICT Innovations held in September 2014, in Ohrid, Macedonia, with main topic World of data. The conference gathered academics, professionals and practitioners in developing solutions and systems in the industrial and business arena, especially innovative commercial implementations, novel applications of technology, and experience in applying recent ICT research advances to practical solutions.
Download or read book Advanced Healthcare Systems written by Rohit Tanwar and published by John Wiley & Sons. This book was released on 2022-03-02 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: ADVANCED HEALTHCARE SYSTEMS This book offers a complete package involving the incubation of machine learning, AI, and IoT in healthcare that is beneficial for researchers, healthcare professionals, scientists, and technologists. The applications and challenges of machine learning and artificial intelligence in the Internet of Things (IoT) for healthcare applications are comprehensively covered in this book. IoT generates big data of varying data quality; intelligent processing and analysis of this big data are the keys to developing smart IoT applications, thereby making space for machine learning (ML) applications. Due to its computational tools that can substitute for human intelligence in the performance of certain tasks, artificial intelligence (AI) makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. Since IoT platforms provide an interface to gather data from various devices, they can easily be deployed into AI/ML systems. The value of AI in this context is its ability to quickly mesh insights from data and automatically identify patterns and detect anomalies in the data that smart sensors and devices generate—information such as temperature, pressure, humidity, air quality, vibration, and sound—that can be really helpful to rapid diagnosis. Audience This book will be of interest to researchers in artificial intelligence, the Internet of Things, machine learning as well as information technologists working in the healthcare sector.
Download or read book Advances In Pattern Recognition Proceedings Of The 6th International Conference written by Pinakpani Pal and published by World Scientific. This book was released on 2006-12-18 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the latest in the series of ICAPR proceedings on the state-of-the-art of different facets of pattern recognition. These conferences have already carved out a unique position among events attended by the pattern recognition community. The contributions tackle open problems in the classic fields of image and video processing, document analysis and multimedia object retrieval as well as more advanced topics in biometrics speech and signal analysis. Many of the papers focus both on theory and application driven basic research pattern recognition.
Download or read book MRI Atlas of MS Lesions written by M.A. Sahraian and published by Springer Science & Business Media. This book was released on 2007-10-16 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: MRI has become the main paraclinical test in the diagnosis and management of multiple sclerosis. We have demonstrated more than 400 pictures of different typical and atypical MS lesions in this atlas. Each image has a teaching point. New diagnostic criteria and differential diagnosis have been discussed.
