Computational Radiomics For Cancer Characterization
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Computational Radiomics For Cancer Characterization
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Author : Omar Sultan Al-Kadi
language : en
Publisher: Frontiers Media SA
Release Date : 2022-10-21
Computational Radiomics For Cancer Characterization written by Omar Sultan Al-Kadi 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 2022-10-21 with Medical categories.
Computational Methodologies For Solid Tumor Characterization And Outcome Prediction In Volumetric Medical Images
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Author : Thierry Lefebvre
language : en
Publisher:
Release Date : 2020
Computational Methodologies For Solid Tumor Characterization And Outcome Prediction In Volumetric Medical Images written by Thierry Lefebvre and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
"Imaging-based quantification and characterization of tumor phenotypes has been the main goal of numerous efforts in recent years for developing and integrating precision oncology in clinical practice. Identifying optimal quantitative image features and machine learning pipelines for computer-aided diagnosis constitute crucial steps towards the development of reproducible, standardized, and clinically relevant imaging biomarkers of cancer phenotypic characteristics. An “image feature” can be understood as an image-derived descriptor of intensity, shape, texture, etc. In radiomics studies, the main hypothesis is that combining many of these quantitative features extracted from tumor regions in medical images can predict underlying genetic or pathological changes occurring in response to disease activity. Given the high variability of processing pipelines in radiomics studies, we first aimed to develop and validate a standardized, IBSI-compliant, and evidence-based processing pipeline for radiomics studies. Second, we aimed to evaluate the diagnostic performance of the well-established robust set of rotationally invariant features from spherical harmonics (SPHARM) decompositions in predicting outcomes from volumetric medical images and compare it to radiomics. Pipelines for these two methods were built and validated on synthetic 3D texture datasets and in two distinct dual-centre diagnostic retrospective studies: i) a study on identifying renal cysts malignancy on contrast-enhanced CT, and ii) a study on identifying histopathological features of endometrial cancer on multi-parametric MRI.For distinguishing benign from malignant renal cysts, a random forest model based on a set of five most discriminative and reproducible radiomics features resulted in high diagnostic performance (testing area under the receiver operating characteristic curve [AUC] = 0.91). Similarly, for SPHARM decomposition coefficients, a tensor logistic regressor resulted in good diagnostic performance for predicting malignancy of renal cysts (testing AUC = 0.83). For detecting histopathological deep myometrial invasion in endometrial cancer on multi-parametric MRI, a random forest model based on our set of five most discriminative and reproducible radiomics features resulted in good diagnostic performance (testing AUC = 0.81). For SPHARM decomposition coefficients, a tensor logistic regressor resulted in higher diagnostic performance using only dynamic-contrast-enhanced MRI images (testing AUC = 0.86). Furthermore, we show that in specific situations, approximate spherical tumor segmentations can rival or even outperform painstakingly obtained but accurate tumor segmentations. Both radiomics features and SPHARM descriptors show promise as reproducible surrogate biomarkers of histopathological features of cancer activity on CT and MRI. Implementing such computational pipelines in clinical practice could improve and accelerate patients’ stratification and decision-making for radiologists and radio-oncologists in cancer diagnosis or treatment"--
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
Advanced Computational Methods For Oncological Image Analysis
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Author : Leonardo Rundo
language : en
Publisher: Mdpi AG
Release Date : 2021-12-06
Advanced Computational Methods For Oncological Image Analysis written by Leonardo Rundo and has been published by Mdpi AG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-06 with Science categories.
Cancer is the second most common cause of death worldwide and encompasses highly variable clinical and biological scenarios. Some of the current clinical challenges are (i) early diagnosis of the disease and (ii) precision medicine, which allows for treatments targeted to specific clinical cases. The ultimate goal is to optimize the clinical workflow by combining accurate diagnosis with the most suitable therapies. Toward this, large-scale machine learning research can define associations among clinical, imaging, and multi-omics studies, making it possible to provide reliable diagnostic and prognostic biomarkers for precision oncology. Such reliable computer-assisted methods (i.e., artificial intelligence) together with clinicians' unique knowledge can be used to properly handle typical issues in evaluation/quantification procedures (i.e., operator dependence and time-consuming tasks). These technical advances can significantly improve result repeatability in disease diagnosis and guide toward appropriate cancer care. Indeed, the need to apply machine learning and computational intelligence techniques has steadily increased to effectively perform image processing operations-such as segmentation, co-registration, classification, and dimensionality reduction-and multi-omics data integration.
Radiomics And Radiogenomics In Neuro Oncology
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Author : Hassan Mohy-ud-Din
language : en
Publisher: Springer Nature
Release Date : 2020-02-24
Radiomics And Radiogenomics In Neuro Oncology written by Hassan Mohy-ud-Din and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-24 with Computers categories.
This book constitutes the proceedings of the First International Workshop on Radiomics and Radiogenomics in Neuro-oncology, RNO-AI 2019, which was held in conjunction with MICCAI in Shenzhen, China, in October 2019. The 10 full papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with the development of tools that can automate the analysis and synthesis of neuro-oncologic imaging.
Radioguided Surgery
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Author : Giuliano Mariani
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-05-10
Radioguided Surgery written by Giuliano Mariani 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 2010-05-10 with Medical categories.
This multidisciplinary textbook is designed to be the standard on the subject and is geared for use by physicians who are involved in the care and/or diagnosis of cancer patients. Comprehensive coverage is provided on all aspects of radioguided surgery. Practical information is readily accessible and throughout there is an emphasis on improved decision making. Tables present the indications, performance, and interpretation of procedures at a glance. A wealth of illustrations, including a full-color insert, enhances the application of new concepts.
Toward Precision Medicine
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Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 2012-01-16
Toward Precision Medicine written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-16 with Medical categories.
Motivated by the explosion of molecular data on humans-particularly data associated with individual patients-and the sense that there are large, as-yet-untapped opportunities to use this data to improve health outcomes, Toward Precision Medicine explores the feasibility and need for "a new taxonomy of human disease based on molecular biology" and develops a potential framework for creating one. The book says that a new data network that integrates emerging research on the molecular makeup of diseases with clinical data on individual patients could drive the development of a more accurate classification of diseases and ultimately enhance diagnosis and treatment. The "new taxonomy" that emerges would define diseases by their underlying molecular causes and other factors in addition to their traditional physical signs and symptoms. The book adds that the new data network could also improve biomedical research by enabling scientists to access patients' information during treatment while still protecting their rights. This would allow the marriage of molecular research and clinical data at the point of care, as opposed to research information continuing to reside primarily in academia. Toward Precision Medicine notes that moving toward individualized medicine requires that researchers and health care providers have access to very large sets of health- and disease-related data linked to individual patients. These data are also critical for developing the information commons, the knowledge network of disease, and ultimately the new taxonomy.
Computational Mathematics Modeling In Cancer Analysis
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Author : Wenjian Qin
language : en
Publisher: Springer Nature
Release Date : 2022-09-22
Computational Mathematics Modeling In Cancer Analysis written by Wenjian Qin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-22 with Computers categories.
This book constitutes the proceedings of the First Workshop on Computational Mathematics Modeling in Cancer Analysis (CMMCA2022), held in conjunction with MICCAI 2022, in Singapore in September 2022. Due to the COVID-19 pandemic restrictions, the CMMCA2022 was held virtually. DALI 2022 accepted 15 papers from the 16 submissions that were reviewed. A major focus of CMMCA2022 is to identify new cutting-edge techniques and their applications in cancer data analysis in response to trends and challenges in theoretical, computational and applied aspects of mathematics in cancer data analysis.
Precision Medicine For Investigators Practitioners And Providers
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Author : Joel Faintuch
language : en
Publisher: Academic Press
Release Date : 2019-11-16
Precision Medicine For Investigators Practitioners And Providers written by Joel Faintuch and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-16 with Science categories.
Precision Medicine for Investigators, Practitioners and Providers addresses the needs of investigators by covering the topic as an umbrella concept, from new drug trials to wearable diagnostic devices, and from pediatrics to psychiatry in a manner that is up-to-date and authoritative. Sections include broad coverage of concerning disease groups and ancillary information about techniques, resources and consequences. Moreover, each chapter follows a structured blueprint, so that multiple, essential items are not overlooked. Instead of simply concentrating on a limited number of extensive and pedantic coverages, scholarly diagrams are also included. Provides a three-pronged approach to precision medicine that is focused on investigators, practitioners and healthcare providers Covers disease groups and ancillary information about techniques, resources and consequences Follows a structured blueprint, ensuring essential chapters items are not overlooked
Neural Networks And Statistical Learning
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Author : Ke-Lin Du
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-09
Neural Networks And Statistical Learning written by Ke-Lin Du 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 2013-12-09 with Technology & Engineering categories.
Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content. Each of the twenty-five chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardware implementations, and some machine learning topics. Applications to biometric/bioinformatics and data mining are also included. Focusing on the prominent accomplishments and their practical aspects, academic and technical staff, graduate students and researchers will find that this provides a solid foundation and encompassing reference for the fields of neural networks, pattern recognition, signal processing, machine learning, computational intelligence, and data mining.