Clinical Image Based Procedures Fairness Of Ai In Medical Imaging And Ethical And Philosophical Issues In Medical Imaging

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Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging

Stefan Wesarg,Esther Puyol Antón,John S. H. Baxter,Marius Erdt,Klaus Drechsler,Cristina Oyarzun Laura,Moti Freiman,Yufei Chen,Islem Rekik,Roy Eagleson,Aasa Feragen,Andrew P. King,Veronika Cheplygina,Melani Ganz-Benjaminsen,Enzo Ferrante,Ben Glocker,Daniel Moyer,Eikel Petersen
Clinical Image Based Procedures Fairness of AI in Medical Imaging and Ethical and Philosophical Issues in Medical Imaging Book PDF

Author : Stefan Wesarg,Esther Puyol Antón,John S. H. Baxter,Marius Erdt,Klaus Drechsler,Cristina Oyarzun Laura,Moti Freiman,Yufei Chen,Islem Rekik,Roy Eagleson,Aasa Feragen,Andrew P. King,Veronika Cheplygina,Melani Ganz-Benjaminsen,Enzo Ferrante,Ben Glocker,Daniel Moyer,Eikel Petersen
Publisher : Springer Nature
Page : 328 pages
File Size : 50,7 Mb
Release : 2023-10-09
Category : Computers
ISBN : 9783031452499

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Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging by Stefan Wesarg,Esther Puyol Antón,John S. H. Baxter,Marius Erdt,Klaus Drechsler,Cristina Oyarzun Laura,Moti Freiman,Yufei Chen,Islem Rekik,Roy Eagleson,Aasa Feragen,Andrew P. King,Veronika Cheplygina,Melani Ganz-Benjaminsen,Enzo Ferrante,Ben Glocker,Daniel Moyer,Eikel Petersen Pdf

This book constitutes the refereed proceedings of the 12th International Workshop on Clinical Image-Based Procedures, CLIP 2023, the First MICCAI Workshop on Fairness of AI in Medical Imaging, FAIMI 2023, and the Second MICCAI Workshop on the Ethical and Philosophical Issues in Medical Imaging, EPIMI 2023, held in conjunction with MICCAI 2023, in October 2023. CLIP 2023 accepted 5 full papers and 3 short papers form 8 submissions received. It focuses on holistic patient models for personalized healthcare with the goal to bring basic research methods closer to the clinical practice. For FAIMI 2023, 19 full papers have been accepted from 20 submissions. They focus on creating awareness about potential fairness issues that can emerge in the context of machine learning. And for EPIMI 2023, 2 papers have been accepted from 5 submissions. They investigate questions that underlie medical imaging research at the most fundamental level.

Ethical and Philosophical Issues in Medical Imaging, Multimodal Learning and Fusion Across Scales for Clinical Decision Support, and Topological Data Analysis for Biomedical Imaging

John S. H. Baxter,Islem Rekik,Roy Eagleson,Luping Zhou,Tanveer Syeda-Mahmood,Hongzhi Wang,Mustafa Hajij
Ethical and Philosophical Issues in Medical Imaging Multimodal Learning and Fusion Across Scales for Clinical Decision Support and Topological Data Analysis for Biomedical Imaging Book PDF

Author : John S. H. Baxter,Islem Rekik,Roy Eagleson,Luping Zhou,Tanveer Syeda-Mahmood,Hongzhi Wang,Mustafa Hajij
Publisher : Springer Nature
Page : 144 pages
File Size : 46,6 Mb
Release : 2022-12-20
Category : Computers
ISBN : 9783031232237

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Ethical and Philosophical Issues in Medical Imaging, Multimodal Learning and Fusion Across Scales for Clinical Decision Support, and Topological Data Analysis for Biomedical Imaging by John S. H. Baxter,Islem Rekik,Roy Eagleson,Luping Zhou,Tanveer Syeda-Mahmood,Hongzhi Wang,Mustafa Hajij Pdf

This book constitutes the refereed joint proceedings of the 1st International Workshop on Ethical & Philosophical Issues in Medical Imaging (EPIMI 2022); the 12th International Workshop on Multimodal Learning and Fusion Across Scales for Clinical Decision Support (ML-CDS 2022) and the 2nd International Workshop on Topological Data Analysis for Biomedical Imaging (TDA4BiomedicalImaging 2022), held in conjunction with the 25th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2022, in Singapore, in September 2022. EPIMI includes five short papers about various humanistic aspects of medical image computing and computer-assisted interventions. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. The TDA papers focus on Topological Data Analysis: a collection of techniques and tools that have matured from an increasing interest in the role topology plays in machine learning and data science.

Artificial Intelligence in Medical Imaging

Lia Morra,Silvia Delsanto,Loredana Correale
Artificial Intelligence in Medical Imaging Book PDF

Author : Lia Morra,Silvia Delsanto,Loredana Correale
Publisher : CRC Press
Page : 162 pages
File Size : 54,8 Mb
Release : 2019-11-25
Category : Science
ISBN : 9781000753202

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Artificial Intelligence in Medical Imaging by Lia Morra,Silvia Delsanto,Loredana Correale Pdf

This book, written by authors with more than a decade of experience in the design and development of artificial intelligence (AI) systems in medical imaging, will guide readers in the understanding of one of the most exciting fields today. After an introductory description of classical machine learning techniques, the fundamentals of deep learning are explained in a simple yet comprehensive manner. The book then proceeds with a historical perspective of how medical AI developed in time, detailing which applications triumphed and which failed, from the era of computer aided detection systems on to the current cutting-edge applications in deep learning today, which are starting to exhibit on-par performance with clinical experts. In the last section, the book offers a view on the complexity of the validation of artificial intelligence applications for commercial use, describing the recently introduced concept of software as a medical device, as well as good practices and relevant considerations for training and testing machine learning systems for medical use. Open problematics on the validation for public use of systems which by nature continuously evolve through new data is also explored. The book will be of interest to graduate students in medical physics, biomedical engineering and computer science, in addition to researchers and medical professionals operating in the medical imaging domain, who wish to better understand these technologies and the future of the field. Features: An accessible yet detailed overview of the field Explores a hot and growing topic Provides an interdisciplinary perspective

Clinical Image-Based Procedures. Translational Research in Medical Imaging

Cristina Oyarzun Laura,Raj Shekhar,Stefan Wesarg,Miguel Ángel González Ballester,Klaus Drechsler,Yoshinobu Sato,Marius Erdt,Marius George Linguraru
Clinical Image Based Procedures Translational Research in Medical Imaging Book PDF

Author : Cristina Oyarzun Laura,Raj Shekhar,Stefan Wesarg,Miguel Ángel González Ballester,Klaus Drechsler,Yoshinobu Sato,Marius Erdt,Marius George Linguraru
Publisher : Springer
Page : 132 pages
File Size : 53,8 Mb
Release : 2016-03-29
Category : Computers
ISBN : 9783319318080

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Clinical Image-Based Procedures. Translational Research in Medical Imaging by Cristina Oyarzun Laura,Raj Shekhar,Stefan Wesarg,Miguel Ángel González Ballester,Klaus Drechsler,Yoshinobu Sato,Marius Erdt,Marius George Linguraru Pdf

This book constitutes revised selected papers from the 4th International Workshop on Clinical Image-Based Procedures, CLIP 2015, held in conjunction with MICCAI 2015 in Munich, Germany, in October 2015. The 15 papers presented in this volume were carefully reviewed and selected from 22 submissions. CLIP focuses on translational research; therefore, the goal of the works presented in this workshop is to bring basic research methods closer to the clinical practice. A highlight of this workshop is the subject of strategies for personalized medicine to enhance diagnosis, treatment and interventions.

Clinical Image-Based Procedures. Translational Research in Medical Imaging

Marius George Linguraru,Cristina Oyarzun Laura,Raj Shekhar,Stefan Wesarg,Miguel Ángel González Ballester,Klaus Drechsler,Yoshinobu Sato,Marius Erdt
Clinical Image Based Procedures Translational Research in Medical Imaging Book PDF

Author : Marius George Linguraru,Cristina Oyarzun Laura,Raj Shekhar,Stefan Wesarg,Miguel Ángel González Ballester,Klaus Drechsler,Yoshinobu Sato,Marius Erdt
Publisher : Springer
Page : 160 pages
File Size : 46,8 Mb
Release : 2014-12-08
Category : Computers
ISBN : 9783319139098

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Clinical Image-Based Procedures. Translational Research in Medical Imaging by Marius George Linguraru,Cristina Oyarzun Laura,Raj Shekhar,Stefan Wesarg,Miguel Ángel González Ballester,Klaus Drechsler,Yoshinobu Sato,Marius Erdt Pdf

This book constitutes revised selected papers from the Third International Workshop on Clinical Image-Based Procedures, CLIP 2014, held in conjunction with MICCAI 2014 in Boston, MA, USA, in September 2014. The 19 papers presented in this volume were carefully reviewed and selected from 26 submissions. New strategies are essential to ensure a smooth and effective translation of computational image-based techniques into the clinic. For these reasons CLIP 2014’s major focus is on translational research filling the gaps between basic science and clinical applications. A highlight of the workshop is the subject of strategies for personalized medicine to enhance diagnosis, treatment and interventions. Authors are encouraged to submit work centered on specific clinical applications, including techniques and procedures based on comprehensive clinical image data. Submissions related to applications already in use and evaluated by clinical users are particularly encouraged. The event will bring together world-class specialists to present ways to strengthen links between computer scientists and engineers, and clinicians.

Artificial Intelligence in Medical Imaging

Erik R. Ranschaert,Sergey Morozov,Paul R. Algra
Artificial Intelligence in Medical Imaging Book PDF

Author : Erik R. Ranschaert,Sergey Morozov,Paul R. Algra
Publisher : Springer
Page : 373 pages
File Size : 47,6 Mb
Release : 2019-01-29
Category : Medical
ISBN : 9783319948782

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Artificial Intelligence in Medical Imaging by Erik R. Ranschaert,Sergey Morozov,Paul R. Algra Pdf

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.

Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging

Kenji Suzuki,Yisong Chen
Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging Book PDF

Author : Kenji Suzuki,Yisong Chen
Publisher : Springer
Page : 387 pages
File Size : 55,9 Mb
Release : 2018-01-09
Category : Technology & Engineering
ISBN : 9783319688435

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Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging by Kenji Suzuki,Yisong Chen Pdf

This book offers the first comprehensive overview of artificial intelligence (AI) technologies in decision support systems for diagnosis based on medical images, presenting cutting-edge insights from thirteen leading research groups around the world. Medical imaging offers essential information on patients’ medical condition, and clues to causes of their symptoms and diseases. Modern imaging modalities, however, also produce a large number of images that physicians have to accurately interpret. This can lead to an “information overload” for physicians, and can complicate their decision-making. As such, intelligent decision support systems have become a vital element in medical-image-based diagnosis and treatment. Presenting extensive information on this growing field of AI, the book offers a valuable reference guide for professors, students, researchers and professionals who want to learn about the most recent developments and advances in the field.

Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures

Hayit Greenspan,Ryutaro Tanno,Marius Erdt,Tal Arbel,Christian Baumgartner,Adrian Dalca,Carole H. Sudre,William M. Wells,Klaus Drechsler,Marius George Linguraru,Cristina Oyarzun Laura,Raj Shekhar,Stefan Wesarg,Miguel Ángel González Ballester
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image Based Procedures Book PDF

Author : Hayit Greenspan,Ryutaro Tanno,Marius Erdt,Tal Arbel,Christian Baumgartner,Adrian Dalca,Carole H. Sudre,William M. Wells,Klaus Drechsler,Marius George Linguraru,Cristina Oyarzun Laura,Raj Shekhar,Stefan Wesarg,Miguel Ángel González Ballester
Publisher : Springer Nature
Page : 192 pages
File Size : 49,7 Mb
Release : 2019-10-10
Category : Computers
ISBN : 9783030326890

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Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures by Hayit Greenspan,Ryutaro Tanno,Marius Erdt,Tal Arbel,Christian Baumgartner,Adrian Dalca,Carole H. Sudre,William M. Wells,Klaus Drechsler,Marius George Linguraru,Cristina Oyarzun Laura,Raj Shekhar,Stefan Wesarg,Miguel Ángel González Ballester Pdf

This book constitutes the refereed proceedings of the First International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2019, and the 8th International Workshop on Clinical Image-Based Procedures, CLIP 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. For UNSURE 2019, 8 papers from 15 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world. CLIP 2019 accepted 11 papers from the 15 submissions received. The workshops provides a forum for work centred on specific clinical applications, including techniques and procedures based on comprehensive clinical image and other data.

Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning

Cristina Oyarzun Laura,M. Jorge Cardoso,Michal Rosen-Zvi,Georgios Kaissis,Marius George Linguraru,Raj Shekhar,Stefan Wesarg,Marius Erdt,Klaus Drechsler,Yufei Chen,Shadi Albarqouni,Spyridon Bakas,Bennett Landman,Nicola Rieke,Holger Roth,Xiaoxiao Li,Daguang Xu,Maria Gabrani,Ender Konukoglu,Michal Guindy,Daniel Rueckert,Alexander Ziller,Dmitrii Usynin,Jonathan Passerat-Palmbach
Clinical Image Based Procedures Distributed and Collaborative Learning Artificial Intelligence for Combating COVID 19 and Secure and Privacy Preserving Machine Learning Book PDF

Author : Cristina Oyarzun Laura,M. Jorge Cardoso,Michal Rosen-Zvi,Georgios Kaissis,Marius George Linguraru,Raj Shekhar,Stefan Wesarg,Marius Erdt,Klaus Drechsler,Yufei Chen,Shadi Albarqouni,Spyridon Bakas,Bennett Landman,Nicola Rieke,Holger Roth,Xiaoxiao Li,Daguang Xu,Maria Gabrani,Ender Konukoglu,Michal Guindy,Daniel Rueckert,Alexander Ziller,Dmitrii Usynin,Jonathan Passerat-Palmbach
Publisher : Springer Nature
Page : 201 pages
File Size : 54,6 Mb
Release : 2021-11-13
Category : Computers
ISBN : 9783030908744

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Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning by Cristina Oyarzun Laura,M. Jorge Cardoso,Michal Rosen-Zvi,Georgios Kaissis,Marius George Linguraru,Raj Shekhar,Stefan Wesarg,Marius Erdt,Klaus Drechsler,Yufei Chen,Shadi Albarqouni,Spyridon Bakas,Bennett Landman,Nicola Rieke,Holger Roth,Xiaoxiao Li,Daguang Xu,Maria Gabrani,Ender Konukoglu,Michal Guindy,Daniel Rueckert,Alexander Ziller,Dmitrii Usynin,Jonathan Passerat-Palmbach Pdf

This book constitutes the refereed proceedings of the 10th International Workshop on Clinical Image-Based Procedures, CLIP 2021, Second MICCAI Workshop on Distributed and Collaborative Learning, DCL 2021, First MICCAI Workshop, LL-COVID19, First Secure and Privacy-Preserving Machine Learning for Medical Imaging Workshop and Tutorial, PPML 2021, held in conjunction with MICCAI 2021, in October 2021. The workshops were planned to take place in Strasbourg, France, but were held virtually due to the COVID-19 pandemic. CLIP 2021 accepted 9 papers from the 13 submissions received. It focuses on holistic patient models for personalized healthcare with the goal to bring basic research methods closer to the clinical practice. For DCL 2021, 4 papers from 7 submissions were accepted for publication. They deal with machine learning applied to problems where data cannot be stored in centralized databases and information privacy is a priority. LL-COVID19 2021 accepted 2 papers out of 3 submissions dealing with the use of AI models in clinical practice. And for PPML 2021, 2 papers were accepted from a total of 6 submissions, exploring the use of privacy techniques in the medical imaging community.

AI Innovation in Medical Imaging Diagnostics

Anbarasan, Kalaivani
AI Innovation in Medical Imaging Diagnostics Book PDF

Author : Anbarasan, Kalaivani
Publisher : IGI Global
Page : 248 pages
File Size : 44,5 Mb
Release : 2021-01-01
Category : Medical
ISBN : 9781799830931

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AI Innovation in Medical Imaging Diagnostics by Anbarasan, Kalaivani Pdf

Recent advancements in the technology of medical imaging, such as CT and MRI scanners, are making it possible to create more detailed 3D and 4D images. These powerful images require vast amounts of digital data to help with the diagnosis of the patient. Artificial intelligence (AI) must play a vital role in supporting with the analysis of this medical imaging data, but it will only be viable as long as healthcare professionals and AI interact to embrace deep thinking platforms such as automation in the identification of diseases in patients. AI Innovation in Medical Imaging Diagnostics is an essential reference source that examines AI applications in medical imaging that can transform hospitals to become more efficient in the management of patient treatment plans through the production of faster imaging and the reduction of radiation dosages through the PET and SPECT imaging modalities. The book also explores how data clusters from these images can be translated into small data packages that can be accessed by healthcare departments to give a real-time insight into patient care and required interventions. Featuring research on topics such as assistive healthcare, cancer detection, and machine learning, this book is ideally designed for healthcare administrators, radiologists, data analysts, computer science professionals, medical imaging specialists, diagnosticians, medical professionals, researchers, and students.

Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing

Rohit Raja,Sandeep Kumar,Shilpa Rani,K. Ramya Laxmi
Artificial Intelligence and Machine Learning in 2D 3D Medical Image Processing Book PDF

Author : Rohit Raja,Sandeep Kumar,Shilpa Rani,K. Ramya Laxmi
Publisher : CRC Press
Page : 215 pages
File Size : 52,6 Mb
Release : 2020-12-22
Category : Medical
ISBN : 9781000337075

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Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing by Rohit Raja,Sandeep Kumar,Shilpa Rani,K. Ramya Laxmi Pdf

Digital images have several benefits, such as faster and inexpensive processing cost, easy storage and communication, immediate quality assessment, multiple copying while preserving quality, swift and economical reproduction, and adaptable manipulation. Digital medical images play a vital role in everyday life. Medical imaging is the process of producing visible images of inner structures of the body for scientific and medical study and treatment as well as a view of the function of interior tissues. This process pursues disorder identification and management. Medical imaging in 2D and 3D includes many techniques and operations such as image gaining, storage, presentation, and communication. The 2D and 3D images can be processed in multiple dimensions. Depending on the requirement of a specific problem, one must identify various features of 2D or 3D images while applying suitable algorithms. These image processing techniques began in the 1960s and were used in such fields as space, clinical purposes, the arts, and television image improvement. In the 1970s, with the development of computer systems, the cost of image processing was reduced and processes became faster. In the 2000s, image processing became quicker, inexpensive, and simpler. In the 2020s, image processing has become a more accurate, more efficient, and self-learning technology. This book highlights the framework of the robust and novel methods for medical image processing techniques in 2D and 3D. The chapters explore existing and emerging image challenges and opportunities in the medical field using various medical image processing techniques. The book discusses real-time applications for artificial intelligence and machine learning in medical image processing. The authors also discuss implementation strategies and future research directions for the design and application requirements of these systems. This book will benefit researchers in the medical image processing field as well as those looking to promote the mutual understanding of researchers within different disciplines that incorporate AI and machine learning. FEATURES Highlights the framework of robust and novel methods for medical image processing techniques Discusses implementation strategies and future research directions for the design and application requirements of medical imaging Examines real-time application needs Explores existing and emerging image challenges and opportunities in the medical field

Clinical Image-Based Procedures. Translational Research in Medical Imaging

Raj Shekhar,Stefan Wesarg,Miguel Ángel González Ballester,Klaus Drechsler,Yoshinobu Sato,Marius Erdt,Marius George Linguraru,Cristina Oyarzun Laura
Clinical Image Based Procedures Translational Research in Medical Imaging Book PDF

Author : Raj Shekhar,Stefan Wesarg,Miguel Ángel González Ballester,Klaus Drechsler,Yoshinobu Sato,Marius Erdt,Marius George Linguraru,Cristina Oyarzun Laura
Publisher : Springer
Page : 85 pages
File Size : 46,5 Mb
Release : 2016-10-14
Category : Computers
ISBN : 9783319464725

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Clinical Image-Based Procedures. Translational Research in Medical Imaging by Raj Shekhar,Stefan Wesarg,Miguel Ángel González Ballester,Klaus Drechsler,Yoshinobu Sato,Marius Erdt,Marius George Linguraru,Cristina Oyarzun Laura Pdf

This book constitutes the revised selected papers from the 5th International Workshop on Clinical Image-Based Procedures, CLIP 2016, held in conjunction with MICCAI 2016 in Athens, Greece, in October 2016. The 10 papers presented in this volume were carefully reviewed and selected from 16 submissions. Specific topics include various image segmentation and registration techniques, applied to various parts of the body. They range from interventional planning to navigation of devices and navigation to the anatomy of interest. Clinical applications cover the skull, the cochlea, cranial nerves, the aortic valve, wrists, and the abdomen, among others.

Artificial Intelligence in Medical Imaging

Erik R. Ranschaert,Sergey Morozov,P. R. Algra
Artificial Intelligence in Medical Imaging Book PDF

Author : Erik R. Ranschaert,Sergey Morozov,P. R. Algra
Publisher : Unknown
Page : 373 pages
File Size : 41,8 Mb
Release : 2019
Category : Artificial intelligence
ISBN : 3319948792

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Artificial Intelligence in Medical Imaging by Erik R. Ranschaert,Sergey Morozov,P. R. Algra Pdf

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.

Clinical Image-Based Procedures. Translational Research in Medical Imaging

Marius Erdt,Marius George Linguraru,Cristina Oyarzun Laura,Raj Shekhar,Stefan Wesarg,Miguel Angel González Ballester,Klaus Drechsler
Clinical Image Based Procedures Translational Research in Medical Imaging Book PDF

Author : Marius Erdt,Marius George Linguraru,Cristina Oyarzun Laura,Raj Shekhar,Stefan Wesarg,Miguel Angel González Ballester,Klaus Drechsler
Publisher : Springer
Page : 171 pages
File Size : 42,8 Mb
Release : 2014-03-28
Category : Computers
ISBN : 9783319056661

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Clinical Image-Based Procedures. Translational Research in Medical Imaging by Marius Erdt,Marius George Linguraru,Cristina Oyarzun Laura,Raj Shekhar,Stefan Wesarg,Miguel Angel González Ballester,Klaus Drechsler Pdf

This book constitutes revised selected papers from the International Workshop on Clinical Image-Based Procedures, CLIP 2013, held in conjunction with MICCAI 2012 in Nagoya, Japan, in September 2013. The 19 papers presented in this volume were carefully reviewed and selected from 26 submissions. The workshop was a productive and exciting forum for the discussion and dissemination of clinically tested, state-of-the-art methods for image-based planning, monitoring and evaluation of medical procedures.

Applications of Artificial Intelligence in Medical Imaging

Abdulhamit Subasi
Applications of Artificial Intelligence in Medical Imaging Book PDF

Author : Abdulhamit Subasi
Publisher : Academic Press
Page : 381 pages
File Size : 44,8 Mb
Release : 2022-11-10
Category : Science
ISBN : 9780443184512

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Applications of Artificial Intelligence in Medical Imaging by Abdulhamit Subasi Pdf

Applications of Artificial Intelligence in Medical Imaging provides the description of various biomedical image analysis in disease detection using AI that can be used to incorporate knowledge obtained from different medical imaging devices such as CT, X-ray, PET and ultrasound. The book discusses the use of AI for detection of several cancer types, including brain tumor, breast, pancreatic, rectal, lung colon, and skin. In addition, it explains how AI and deep learning techniques can be used to diagnose Alzheimer's, Parkinson's, COVID-19 and mental conditions. This is a valuable resource for clinicians, researchers and healthcare professionals who are interested in learning more about AI and its impact in medical/biomedical image analysis. Discusses new deep learning algorithms for image analysis and how they are used for medical images Provides several examples for each imaging technique, along with their application areas so that readers can rely on them as a clinical decision support system Describes how new AI tools may contribute significantly to the successful enhancement of a single patient's clinical knowledge to improve treatment outcomes