Automated Segmentation Of Head And Neck Cancer Using Texture Analysis With Co Registered Pet Ct Images
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Automated Segmentation Of Head And Neck Cancer Using Texture Analysis With Co Registered Pet Ct Images
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Author : Huan Yu
language : en
Publisher:
Release Date : 2010
Automated Segmentation Of Head And Neck Cancer Using Texture Analysis With Co Registered Pet Ct Images written by Huan Yu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
Radiation therapy is often offered as the primary treatment for head and neck cancer(HNC). Accurate target delineation is essential for the success of radiation therapy. The current target definition technique - manual delineation using Computed Tomography(CT) - is subject to high observer variability. Functional imaging modalities such as 2-[18F]-fluoro-2-deoxy-D-glucose Positron Emission Tomography(FDG-PET) can greatly improve the visualization of tumor. FDG-PET co-registered with CT has shown potential to improve the accuracy of target localization and reduce observer variability. Unfortunately, due to the limitation of PET, the degree of improvement obtained by qualitative and simple quantitative (e.g. thresholding) use of FDG-PET is not ideal. However, both PET and CT images contain a wealth of texture information that could be used to improve the accuracy of target definition. This thesis has investigated using texture analysis techniques to automatically delineate radiation targets. Firstly, PET and CT texture features with high discrimination ability were identified and a texture analysis technique- a decision tree based K Nearest Neighbour(DTKNN) classifier - was developed. DTKNN could accurately classify head and neck tissue with an area under curve(AUC) of a Receiver Operator Characteristic(ROC) of 0.95. Subsequently, an automated target delineation technique - CO-registered Multi-modality Pattern Analysis Segmentation System(COMPASS) - was developed that can delineate tumor on a voxel-by-voxel basis. COMPASS was found to accurately delineate HNC with 84% sensitivity and 95% specificity on a voxel basis per patient. To accurately evaluate the utility of the COMPASS in radiation targeting, a validation method which can combine biased observers' contours to generate a probabilistic reference for validation was developed. The method was based on maximum likelihood analysis using a simulated annealing(SA) algorithm. The results from this thesis show that texture features of both PET and CT images can enhance the discrimination between HNC and normal tissue, and an automated delineation method of HNC using texture analysis of PET and CT images can accurately and consistently define radiation targets in head and neck. This suggests that automated segmentation of radiation targets based on texture analysis techniques may significantly reduce observer variability and improve the accuracy of radiation targeting.
Automatic Segmentation Of Lung Carcinoma Using 3d Texture Features In Co Registered 18 Fdg Pet Ct Images
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Author : Daniel Markel
language : en
Publisher:
Release Date : 2011
Automatic Segmentation Of Lung Carcinoma Using 3d Texture Features In Co Registered 18 Fdg Pet Ct Images written by Daniel Markel and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
Radiomics And Radiogenomics
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Author : Ruijiang Li
language : en
Publisher: CRC Press
Release Date : 2019-07-09
Radiomics And Radiogenomics written by Ruijiang Li and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-09 with Science categories.
Radiomics and Radiogenomics: Technical Basis and Clinical Applications provides a first summary of the overlapping fields of radiomics and radiogenomics, showcasing how they are being used to evaluate disease characteristics and correlate with treatment response and patient prognosis. It explains the fundamental principles, technical bases, and clinical applications with a focus on oncology. The book’s expert authors present computational approaches for extracting imaging features that help to detect and characterize disease tissues for improving diagnosis, prognosis, and evaluation of therapy response. This book is intended for audiences including imaging scientists, medical physicists, as well as medical professionals and specialists such as diagnostic radiologists, radiation oncologists, and medical oncologists. Features Provides a first complete overview of the technical underpinnings and clinical applications of radiomics and radiogenomics Shows how they are improving diagnostic and prognostic decisions with greater efficacy Discusses the image informatics, quantitative imaging, feature extraction, predictive modeling, software tools, and other key areas Covers applications in oncology and beyond, covering all major disease sites in separate chapters Includes an introduction to basic principles and discussion of emerging research directions with a roadmap to clinical translation
Automatic Segmentation Of Lung Carcinoma Using Three Dimensional Texture Features In Co Registered 18 Fdg Pet Ct Images
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Author : Daniel Markel
language : en
Publisher:
Release Date : 2011
Automatic Segmentation Of Lung Carcinoma Using Three Dimensional Texture Features In Co Registered 18 Fdg Pet Ct Images written by Daniel Markel and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
Can be as high as 700% by volume. Robust, automated definition of tumor boundarieshas the ability to significantly improve treatment accuracy and efficiency. However, the information provided in computed tomography (CT) is not sensitive enough to differences between tumor and healthy tissue and positron emission tomography (PET) is hampered by blurriness and low resolution. The textural characteristics of thoracic tissue was investigated and compared with those of tumors found within 21 patient PET and CT images in order to enhance the differences and the boundary between cancerous and healthy tissue. A pattern recognition approach was used from these samples to learn the textural characteristics of each and classify voxels as being either normal or abnormal.highest overlap with that of an oncologist's tumor definition.Variability between oncologists in defining the tumor during radiation therapy planningThe approach was compared to a number of alternative methods and found to have the.
Machine Learning With Radiation Oncology Big Data
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Author : Jun Deng
language : en
Publisher: Frontiers Media SA
Release Date : 2019-01-21
Machine Learning With Radiation Oncology Big Data written by Jun Deng and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-21 with categories.
Image Guided High Precision Radiotherapy
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Author : Esther G. C. Troost
language : en
Publisher: Springer Nature
Release Date : 2022-10-11
Image Guided High Precision Radiotherapy written by Esther G. C. Troost and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-11 with Medical categories.
This book equips readers with detailed knowledge on the current status of image-guided radiotherapy with photons and particles and highlights issues that need to be addressed in order to further improve treatment outcomes. The opening chapters cover clinical and technical aspects of target volume definition using anatomic (computed tomography and magnetic resonance imaging; MRI) as well as functional (MRI and positron emission tomography) imaging. Up-to-date information is then provided on the full range of image-guided high-precision radiotherapy techniques, including IMRT/VMAT, stereotactic body radiation therapy, MR-guided linear accelerators, MR-guided brachytherapy, and particle therapy. The role of ultrasonography in image-guided radiotherapy is discussed, as are the available means for target volume demarcation and stabilization and adaptive radiation therapy. Finally, outcome evaluation is explored in depth, with a particular focus on the role of multimodality imaging in predicting tumor control and normal tissue toxicity. The authors are experts in different specialties and the book will be of high value for radiation oncologists, medical physicists, radiologists, nuclear medicine physicians, and radiation technicians.
Medical Image Understanding And Analysis
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Author : Bartłomiej W. Papież
language : en
Publisher: Springer Nature
Release Date : 2020-07-08
Medical Image Understanding And Analysis written by Bartłomiej W. Papież and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-08 with Computers categories.
This book constitutes the refereed proceedings of the 24th Conference on Medical Image Understanding and Analysis, MIUA 2020, held in July 2020. Due to COVID-19 pandemic the conference was held virtually. The 29 full papers and 5 short papers presented were carefully reviewed and selected from 70 submissions. They were organized according to following topical sections: image segmentation; image registration, reconstruction and enhancement; radiomics, predictive models, and quantitative imaging biomarkers; ocular imaging analysis; biomedical simulation and modelling.
Ict And Critical Infrastructure Proceedings Of The 48th Annual Convention Of Computer Society Of India Vol Ii
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Author : Suresh Chandra Satapathy
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-10-19
Ict And Critical Infrastructure Proceedings Of The 48th Annual Convention Of Computer Society Of India Vol Ii written by Suresh Chandra Satapathy and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-19 with Technology & Engineering categories.
This volume contains 85 papers presented at CSI 2013: 48th Annual Convention of Computer Society of India with the theme “ICT and Critical Infrastructure”. The convention was held during 13th –15th December 2013 at Hotel Novotel Varun Beach, Visakhapatnam and hosted by Computer Society of India, Vishakhapatnam Chapter in association with Vishakhapatnam Steel Plant, the flagship company of RINL, India. This volume contains papers mainly focused on Data Mining, Data Engineering and Image Processing, Software Engineering and Bio-Informatics, Network Security, Digital Forensics and Cyber Crime, Internet and Multimedia Applications and E-Governance Applications.
Information Processing In Medical Imaging
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Author : Gábor Székely
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-29
Information Processing In Medical Imaging written by Gábor Székely and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-29 with Computers categories.
This book constitutes the refereed proceedings of the 22nd International Conference on Information Processing in Medical Imaging, IPMI 2011, held at Kloster Irsee, Germany, in July 2011. The 24 full papers and 39 poster papers included in this volume were carefully reviewed and selected from 224 submissions. The papers are organized in topical sections on segmentation, statistical methods, shape analysis, registration, diffusion imaging, disease progression modeling, and computer aided diagnosis. The poster sessions deal with segmentation, shape analysis, statistical methods, image reconstruction, microscopic image analysis, computer aided diagnosis, diffusion imaging, functional brain analysis, registration and other related topics.
Head And Neck Tumor Segmentation
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Author : Vincent Andrearczyk
language : en
Publisher: Springer Nature
Release Date : 2021-01-12
Head And Neck Tumor Segmentation written by Vincent Andrearczyk and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-12 with Computers categories.
This book constitutes the First 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2020, which was held in conjunction with the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020. The challenge took place virtually due to the COVID-19 pandemic. The 2 full and 8 short papers presented together with an overview paper in this volume were carefully reviewed and selected form numerous submissions. This challenge aims to evaluate and compare the current state-of-the-art methods for automatic head and neck tumor segmentation. In the context of this challenge, a dataset of 204 delineated PET/CT images was made available for training as well as 53 PET/CT images for testing. Various deep learning methods were developed by the participants with excellent results.