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...
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| Format: | Online |
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| Idioma: | anglès |
| Publicat: |
MDPI - Multidisciplinary Digital Publishing Institute
2025
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| Accés en línia: | ONIX_20250812T110751_9783725845156_523 |
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| _version_ | 1869527845100847104 |
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| 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 |