An Automated Modified Region Growing Technique For Prostate Segmentation In Trans Rectal Ultrasound Images

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An Automated Modified Region Growing Technique for Prostate Segmentation in Trans-rectal Ultrasound Images

Author : Marian Wahba
Publisher :
ISBN 13 :
Total Pages : 96 pages
Book Rating : 4.:/5 (613 download)

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Book Synopsis An Automated Modified Region Growing Technique for Prostate Segmentation in Trans-rectal Ultrasound Images by : Marian Wahba

Download or read book An Automated Modified Region Growing Technique for Prostate Segmentation in Trans-rectal Ultrasound Images written by Marian Wahba and published by . This book was released on 2008 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical imaging plays a vital role in the medical field because it is widely used in diseases diagnosis and treatment of patients. There are different modalities of medical imaging such as ultrasounds, x-rays, Computed Tomography (CT), Magnetic Resonance (MR), and Positron Emission Tomography (PET). Most of these modalities usually suffer from noise and other sampling artifacts. The diagnosis process in these modalities depends mainly on the interpretation of the radiologists. Consequently, the diagnosis is subjective as it is based on the radiologist experience. Medical image segmentation is an important process in the field of image processing. It has a significant role in many applications such as diagnosis, therapy planning, and advanced surgeries. There are many segmentation techniques to be applied on medical images. However, most of these techniques are still depending on the experts, especially for initializing the segmentation process. The artifacts of images can affect the segmentation output. In this thesis, we propose a new approach for automatic prostate segmentation of Trans-Rectal UltraSound (TRUS) images by dealing with the speckle not as noise but as informative signals. The new approach is an automation of the conventional region growing technique. The proposed approach overcomes the requirement of manually selecting a seed point for initializing the segmentation process. In addition, the proposed approach depends on unique features such as the intensity and the spatial Euclidean distance to overcome the effect of the speckle noise of the images. The experimental results of the proposed approach show that it is fast and accurate. Moreover, it performs well on the ultrasound images, which has the common problem of the speckle noise.

Automated Modified Region Growing Technique for Ultrasound Images

Author : Marian Wahba
Publisher : LAP Lambert Academic Publishing
ISBN 13 : 9783659222504
Total Pages : 124 pages
Book Rating : 4.2/5 (225 download)

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Book Synopsis Automated Modified Region Growing Technique for Ultrasound Images by : Marian Wahba

Download or read book Automated Modified Region Growing Technique for Ultrasound Images written by Marian Wahba and published by LAP Lambert Academic Publishing. This book was released on 2014-02 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical imaging plays a vital role in the medical field because it is widely used in diseases diagnosis and treatment of patients. There are different modalities of medical imaging such as ultrasounds, x-rays, Computed Tomography (CT), Magnetic Resonance (MR), and Positron Emission Tomography (PET). Most of these modalities usually suffer from noise and other sampling artifacts. The diagnosis process in these modalities depends mainly on the interpretation of the radiologists. Consequently, the diagnosis is subjective as it is based on the radiologist experience. Medical image segmentation is an important process in the field of image processing. It has a significant role in many applications such as diagnosis, therapy planning, and advanced surgeries. In this book, we propose a new approach for automatic prostate segmentation of Trans-Rectal UltraSound (TRUS) images by dealing with the speckle not as noise but as informative signals. The proposed approach overcomes the requirement of manually selecting a seed point for initializing the segmentation process. The experimental results of the proposed approach show that it is fast and accurate.

Prostate Segmentation and Regions of Interest Detection in Transrectal Ultrasound Images

Author : Joseph Awad
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (13 download)

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Book Synopsis Prostate Segmentation and Regions of Interest Detection in Transrectal Ultrasound Images by : Joseph Awad

Download or read book Prostate Segmentation and Regions of Interest Detection in Transrectal Ultrasound Images written by Joseph Awad and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Automatic Prostate Segmentation in Transrectal Ultrasound Images Using Modified V-net Convolutional Neural Network

Author : Filip Paskali
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (126 download)

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Book Synopsis Automatic Prostate Segmentation in Transrectal Ultrasound Images Using Modified V-net Convolutional Neural Network by : Filip Paskali

Download or read book Automatic Prostate Segmentation in Transrectal Ultrasound Images Using Modified V-net Convolutional Neural Network written by Filip Paskali and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Robust Image Segmentation Applied to Magnetic Resonance and Ultrasound Images of the Prostate

Author : Soumya Ghose
Publisher :
ISBN 13 :
Total Pages : 276 pages
Book Rating : 4.:/5 (867 download)

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Book Synopsis Robust Image Segmentation Applied to Magnetic Resonance and Ultrasound Images of the Prostate by : Soumya Ghose

Download or read book Robust Image Segmentation Applied to Magnetic Resonance and Ultrasound Images of the Prostate written by Soumya Ghose and published by . This book was released on 2012 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prostate segmentation in trans rectal ultrasound (TRUS) and magnetic resonanceimages (MRI) facilitates volume estimation, multi-modal image registration, surgicalplaning and image guided prostate biopsies. The objective of this thesis is to developshape and region prior deformable models for accurate, robust and computationallyefficient prostate segmentation in TRUS and MRI images. Primary contributionof this thesis is in adopting a probabilistic learning approach to achieve soft classificationof the prostate for automatic initialization and evolution of a shape andregion prior deformable models for prostate segmentation in TRUS images. Twodeformable models are developed for the purpose. An explicit shape and regionprior deformable model is derived from principal component analysis (PCA) of thecontour landmarks obtained from the training images and PCA of the probabilitydistribution inside the prostate region. Moreover, an implicit deformable model isderived from PCA of the signed distance representation of the labeled training dataand curve evolution is guided by energy minimization framework of Mumford-Shah(MS) functional. Region based energy is determined from region based statistics ofthe posterior probabilities. Graph cut energy minimization framework is adoptedfor prostate segmentation in MRI. Posterior probabilities obtained in a supervisedlearning schema and from a probabilistic segmentation of the prostate using an atlasare fused in logarithmic domain to reduce segmentation error. Finally a graphcut energy minimization in the stochastic framework achieves prostate segmentationin MRI. Statistically significant improvement in segmentation accuracies areachieved compared to some of the works in literature. Stochastic representation ofthe prostate region and use of the probabilities in optimization significantly improvesegmentation accuracies.

Applications of Artificial Intelligence Techniques in Engineering

Author : Hasmat Malik
Publisher : Springer
ISBN 13 : 9811318190
Total Pages : 643 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Applications of Artificial Intelligence Techniques in Engineering by : Hasmat Malik

Download or read book Applications of Artificial Intelligence Techniques in Engineering written by Hasmat Malik and published by Springer. This book was released on 2018-09-28 with total page 643 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a collection of high-quality, peer-reviewed innovative research papers from the International Conference on Signals, Machines and Automation (SIGMA 2018) held at Netaji Subhas Institute of Technology (NSIT), Delhi, India. The conference offered researchers from academic and industry the opportunity to present their original work and exchange ideas, information, techniques and applications in the field of computational intelligence, artificial intelligence and machine intelligence. The book is divided into two volumes discussing a wide variety of industrial, engineering and scientific applications of the emerging techniques.

Deep Learning in Biomedical Signal and Medical Imaging

Author : Ngangbam Herojit Singh
Publisher : CRC Press
ISBN 13 : 1040107117
Total Pages : 274 pages
Book Rating : 4.0/5 (41 download)

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Book Synopsis Deep Learning in Biomedical Signal and Medical Imaging by : Ngangbam Herojit Singh

Download or read book Deep Learning in Biomedical Signal and Medical Imaging written by Ngangbam Herojit Singh and published by CRC Press. This book was released on 2024-09-30 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers detailed information on biomedical imaging using Deep Convolutional Neural Networks (Deep CNN). It focuses on different types of biomedical images to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis and image processing perspectives. Deep Learning in Biomedical Signal and Medical Imaging discusses classification, segmentation, detection, tracking, and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT, and X-RAY, amongst others. It surveys the most recent techniques and approaches in this field, with both broad coverage and enough depth to be of practical use to working professionals. It includes examples of the application of signal and image processing employing Deep CNN to Alzheimer’s, brain tumor, skin cancer, breast cancer, and stroke prediction, as well as ECG and EEG signals. This book offers enough fundamental and technical information on these techniques, approaches, and related problems without overcrowding the reader’s head. It presents the results of the latest investigations in the field of Deep CNN for biomedical data analysis. The techniques and approaches presented in this book deal with the most important and/or the newest topics encountered in this field. They combine the fundamental theory of artificial intelligence (AI), machine learning (ML,) and Deep CNN with practical applications in biology and medicine. Certainly, the list of topics covered in this book is not exhaustive, but these topics will shed light on the implications of the presented techniques and approaches on other topics in biomedical data analysis. The book is written for graduate students, researchers, and professionals in biomedical engineering, electrical engineering, signal process engineering, biomedical imaging, and computer science. The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educators who are working in the context of the topics.

Artificial Intelligence in Medical Imaging

Author : Erik R. Ranschaert
Publisher : Springer
ISBN 13 : 3319948784
Total Pages : 373 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Artificial Intelligence in Medical Imaging by : Erik R. Ranschaert

Download or read book Artificial Intelligence in Medical Imaging written by Erik R. Ranschaert and published by Springer. This book was released on 2019-01-29 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.

Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2012

Author : Nicholas Ayache
Publisher : Springer Science & Business Media
ISBN 13 : 3642334156
Total Pages : 807 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2012 by : Nicholas Ayache

Download or read book Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2012 written by Nicholas Ayache and published by Springer Science & Business Media. This book was released on 2012-09-22 with total page 807 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 7510, 7511, and 7512 constitutes the refereed proceedings of the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012, held in Nice, France, in October 2012. Based on rigorous peer reviews, the program committee carefully selected 252 revised papers from 781 submissions for presentation in three volumes. The first volume includes 91 papers organized in topical sections on abdominal imaging, computer-assisted interventions and robotics; computer-aided diagnosis and planning; image reconstruction and enhancement; analysis of microscopic and optical images; computer-assisted interventions and robotics; image segmentation; cardiovascular imaging; and brain imaging: structure, function and disease evolution.

Medical Image Registration

Author : Joseph V. Hajnal
Publisher : CRC Press
ISBN 13 : 1420042475
Total Pages : 394 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Medical Image Registration by : Joseph V. Hajnal

Download or read book Medical Image Registration written by Joseph V. Hajnal and published by CRC Press. This book was released on 2001-06-27 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image registration is the process of systematically placing separate images in a common frame of reference so that the information they contain can be optimally integrated or compared. This is becoming the central tool for image analysis, understanding, and visualization in both medical and scientific applications. Medical Image Registration provid

Biomedical Data Mining for Information Retrieval

Author : Sujata Dash
Publisher : John Wiley & Sons
ISBN 13 : 111971124X
Total Pages : 450 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Biomedical Data Mining for Information Retrieval by : Sujata Dash

Download or read book Biomedical Data Mining for Information Retrieval written by Sujata Dash and published by John Wiley & Sons. This book was released on 2021-08-24 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: BIOMEDICAL DATA MINING FOR INFORMATION RETRIEVAL This book not only emphasizes traditional computational techniques, but discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. Biomedical Data Mining for Information Retrieval comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally. These images are mainly in the form of computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients’ biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions relating to healthcare. Image mining in medicine can help to uncover new relationships between data and reveal new useful information that can be helpful for doctors in treating their patients. Audience Researchers in various fields including computer science, medical informatics, healthcare IOT, artificial intelligence, machine learning, image processing, clinical big data analytics.

Medical Imaging Informatics

Author : Alex A.T. Bui
Publisher : Springer Science & Business Media
ISBN 13 : 1441903852
Total Pages : 454 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Medical Imaging Informatics by : Alex A.T. Bui

Download or read book Medical Imaging Informatics written by Alex A.T. Bui and published by Springer Science & Business Media. This book was released on 2009-12-01 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical Imaging Informatics provides an overview of this growing discipline, which stems from an intersection of biomedical informatics, medical imaging, computer science and medicine. Supporting two complementary views, this volume explores the fundamental technologies and algorithms that comprise this field, as well as the application of medical imaging informatics to subsequently improve healthcare research. Clearly written in a four part structure, this introduction follows natural healthcare processes, illustrating the roles of data collection and standardization, context extraction and modeling, and medical decision making tools and applications. Medical Imaging Informatics identifies core concepts within the field, explores research challenges that drive development, and includes current state-of-the-art methods and strategies.

Deep Learning and Data Labeling for Medical Applications

Author : Gustavo Carneiro
Publisher : Springer
ISBN 13 : 3319469762
Total Pages : 289 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Deep Learning and Data Labeling for Medical Applications by : Gustavo Carneiro

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.

Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

Author : Anne L. Martel
Publisher : Springer
ISBN 13 : 9783030597122
Total Pages : 785 pages
Book Rating : 4.5/5 (971 download)

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Book Synopsis Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 by : Anne L. Martel

Download or read book Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 written by Anne L. Martel and published by Springer. This book was released on 2020-10-03 with total page 785 pages. Available in PDF, EPUB and Kindle. Book excerpt: The seven-volume set LNCS 12261, 12262, 12263, 12264, 12265, 12266, and 12267 constitutes the refereed proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 542 revised full papers presented were carefully reviewed and selected from 1809 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: machine learning methodologies Part II: image reconstruction; prediction and diagnosis; cross-domain methods and reconstruction; domain adaptation; machine learning applications; generative adversarial networks Part III: CAI applications; image registration; instrumentation and surgical phase detection; navigation and visualization; ultrasound imaging; video image analysis Part IV: segmentation; shape models and landmark detection Part V: biological, optical, microscopic imaging; cell segmentation and stain normalization; histopathology image analysis; opthalmology Part VI: angiography and vessel analysis; breast imaging; colonoscopy; dermatology; fetal imaging; heart and lung imaging; musculoskeletal imaging Part VI: brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; positron emission tomography

Machine Learning in Radiation Oncology

Author : Issam El Naqa
Publisher : Springer
ISBN 13 : 3319183052
Total Pages : 336 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Machine Learning in Radiation Oncology by : Issam El Naqa

Download or read book Machine Learning in Radiation Oncology written by Issam El Naqa and published by Springer. This book was released on 2015-06-19 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.

Atlas of Multiparametric Prostate MRI

Author : Joan C. Vilanova
Publisher : Springer
ISBN 13 : 3319617869
Total Pages : 164 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Atlas of Multiparametric Prostate MRI by : Joan C. Vilanova

Download or read book Atlas of Multiparametric Prostate MRI written by Joan C. Vilanova and published by Springer. This book was released on 2017-09-28 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This atlas provides a comprehensive, state of the art review of the use of multiparametric MRI (mpMRI) for the imaging of prostate cancer, covering aspects from diagnosis and loco-regional staging through to the role of the technique after treatment and follow-up. The book contains a wealth of high-resolution images, many of them in color, and displays the anatomical-MRI–pathological correlation whenever appropriate. Readers will find a helpful overview on the current standardized method for reading and reporting on mpMRI, the Prostate Imaging Reporting and Data System (PI-RADS), version 2. Dedicated chapters focus on differential diagnosis and imaging pitfalls, and the inclusion of helpful diagrams and algorithms will further assist in image interpretation, enabling readers to ease and improve their use of mpMRI. Edited and written by very experienced radiologists, pathologists, and urologists; the Atlas of Multiparametric Prostate MRI will serve as a unique source of clinically relevant information and an aid to disease management for radiologists, urologists, pathologists, radiotherapists, and oncologists.

Convolutional Neural Networks in Visual Computing

Author : Ragav Venkatesan
Publisher : CRC Press
ISBN 13 : 1351650327
Total Pages : 204 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis Convolutional Neural Networks in Visual Computing by : Ragav Venkatesan

Download or read book Convolutional Neural Networks in Visual Computing written by Ragav Venkatesan and published by CRC Press. This book was released on 2017-10-23 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the fundamentals in designing and deploying techniques using deep architectures. It is intended to serve as a beginner's guide to engineers or students who want to have a quick start on learning and/or building deep learning systems. This book provides a good theoretical and practical understanding and a complete toolkit of basic information and knowledge required to understand and build convolutional neural networks (CNN) from scratch. The book focuses explicitly on convolutional neural networks, filtering out other material that co-occur in many deep learning books on CNN topics.