AI in Medical Imaging and Image Processing

This compilation emphasizes the transformative role of artificial intelligence (AI) and machine learning (ML) in the healthcare field, illustrating their potential to refine diagnostics, treatment protocols, and patient management. The studies confront critical healthcare challenges, presenting solu...

Descripció completa

Guardat en:
Dades bibliogràfiques
Format: Online
Idioma:anglès
Publicat: MDPI - Multidisciplinary Digital Publishing Institute 2025
Matèries:
Accés en línia:ONIX_20250812T110751_9783725845156_523
Etiquetes: Afegir etiqueta
Sense etiquetes, Sigues el primer a etiquetar aquest registre!
_version_ 1869527845100847104
collection Directory of Open Access Books
description This compilation emphasizes the transformative role of artificial intelligence (AI) and machine learning (ML) in the healthcare field, illustrating their potential to refine diagnostics, treatment protocols, and patient management. The studies confront critical healthcare challenges, presenting solutions that improve precision, efficiency, and accessibility. Featured are works on enhancing diagnostics, employing models like convolutional neural networks (CNNs) and transformers for the early and accurate identification of various conditions, such as different cancers, stroke, intracranial hemorrhage, and acute aortic syndrome. The collection also delves into AI applications in surgical planning and intraoperative guidance, with research analyzing preoperative imaging predictors and AI tools for detecting surgical wound infections. New AI methodologies for addressing rare and complex diagnoses, such as early-stage osteosarcoma detection, bone mineral density screening in cystic fibrosis, and biomarker identification in leukemia, are included. Additionally, the compilation addresses the practical aspects of AI integration, such as interrater variability, reproducibility, and the necessity for standardized benchmarks. This collection serves as a valuable resource for healthcare professionals, researchers, and technologists aiming to comprehend and utilize AI's potential in medicine.
format Online
id doab-20.500.12854ir-165768
institution Directory of Open Access Books
language eng
publishDate 2025
publishDateRange 2025
publishDateSort 2025
publisher MDPI - Multidisciplinary Digital Publishing Institute
publisherStr MDPI - Multidisciplinary Digital Publishing Institute
record_format ojs
spelling doab-20.500.12854ir-1657682025-08-12T10:15:08Z AI in Medical Imaging and Image Processing Nurzynska, Karolina Strzelecki, Michał Piórkowski, Adam Obuchowicz, Rafał Artificial intelligence Computer-based diagnosis Medical imaging Image analysis Image processing Machine Learning Deep Learning Radiomics thema EDItEUR::M Medicine and Nursing::MK Medical specialties, branches of medicine::MKZ Therapy and therapeutics::MKZV Gene therapy This compilation emphasizes the transformative role of artificial intelligence (AI) and machine learning (ML) in the healthcare field, illustrating their potential to refine diagnostics, treatment protocols, and patient management. The studies confront critical healthcare challenges, presenting solutions that improve precision, efficiency, and accessibility. Featured are works on enhancing diagnostics, employing models like convolutional neural networks (CNNs) and transformers for the early and accurate identification of various conditions, such as different cancers, stroke, intracranial hemorrhage, and acute aortic syndrome. The collection also delves into AI applications in surgical planning and intraoperative guidance, with research analyzing preoperative imaging predictors and AI tools for detecting surgical wound infections. New AI methodologies for addressing rare and complex diagnoses, such as early-stage osteosarcoma detection, bone mineral density screening in cystic fibrosis, and biomarker identification in leukemia, are included. Additionally, the compilation addresses the practical aspects of AI integration, such as interrater variability, reproducibility, and the necessity for standardized benchmarks. This collection serves as a valuable resource for healthcare professionals, researchers, and technologists aiming to comprehend and utilize AI's potential in medicine. 2025-08-12T10:15:06Z 2025-08-12T10:15:06Z 2025 book ONIX_20250812T110751_9783725845156_523 9783725845156 9783725845163 https://directory.doabooks.org/handle/20.500.12854/165768 eng image/jpeg Attribution 4.0 International https://mdpi.com/books https://mdpi.com/books/pdfview/topic/11271 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-4516-3 10.3390/books978-3-7258-4516-3 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725845156 9783725845163 386 open access
spellingShingle Artificial intelligence
Computer-based diagnosis
Medical imaging
Image analysis
Image processing
Machine Learning
Deep Learning
Radiomics
thema EDItEUR::M Medicine and Nursing::MK Medical specialties, branches of medicine::MKZ Therapy and therapeutics::MKZV Gene therapy
AI in Medical Imaging and Image Processing
title AI in Medical Imaging and Image Processing
title_full AI in Medical Imaging and Image Processing
title_fullStr AI in Medical Imaging and Image Processing
title_full_unstemmed AI in Medical Imaging and Image Processing
title_short AI in Medical Imaging and Image Processing
title_sort ai in medical imaging and image processing
topic Artificial intelligence
Computer-based diagnosis
Medical imaging
Image analysis
Image processing
Machine Learning
Deep Learning
Radiomics
thema EDItEUR::M Medicine and Nursing::MK Medical specialties, branches of medicine::MKZ Therapy and therapeutics::MKZV Gene therapy
topic_facet Artificial intelligence
Computer-based diagnosis
Medical imaging
Image analysis
Image processing
Machine Learning
Deep Learning
Radiomics
thema EDItEUR::M Medicine and Nursing::MK Medical specialties, branches of medicine::MKZ Therapy and therapeutics::MKZV Gene therapy
url ONIX_20250812T110751_9783725845156_523