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Proceedings of 2024 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2024): Medical Imaging and Computer-Aided Diagnosis [Kietas viršelis]

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  • Formatas: Hardback, 592 pages, aukštis x plotis: 235x155 mm, 215 Illustrations, color; 23 Illustrations, black and white; XVI, 592 p. 238 illus., 215 illus. in color., 1 Hardback
  • Serija: Lecture Notes in Electrical Engineering 1372
  • Išleidimo metai: 04-Apr-2025
  • Leidėjas: Springer Nature Switzerland AG
  • ISBN-10: 9819638623
  • ISBN-13: 9789819638628
Kitos knygos pagal šią temą:
  • Formatas: Hardback, 592 pages, aukštis x plotis: 235x155 mm, 215 Illustrations, color; 23 Illustrations, black and white; XVI, 592 p. 238 illus., 215 illus. in color., 1 Hardback
  • Serija: Lecture Notes in Electrical Engineering 1372
  • Išleidimo metai: 04-Apr-2025
  • Leidėjas: Springer Nature Switzerland AG
  • ISBN-10: 9819638623
  • ISBN-13: 9789819638628
Kitos knygos pagal šią temą:

This book aims to provide a collaborative platform for leading technology minds to exchange insights, foster interdisciplinary dialogue, and propel advancements in both medical imaging and computer-aided diagnosis. As technology evolves, a plethora of state-of-the-art human imaging devices have made remarkable strides in the medical field, transforming diagnostic and treatment standards. Concurrently, there is a growing emphasis on extracting and deciphering extensive information from medical images, spurring the demand for innovative solutions. The fusion of digital image processing and computer vision technologies has paved the way for computer-aided diagnosis (CAD), a pivotal player in disease analysis. This conference extends a warm invitation to researchers, scholars, engineers, scientists, industry leaders, and graduate students active in these fields. Through diverse participation formats, including compelling poster presentations and enlightening oral sessions, attendees will gain profound insights into the intricate interplay between these realms. This book showcases the latest technological breakthroughs, forging valuable connections and envisioning future applications.

.- 1 Oral Cancer Classification using a Hybrid Attention-aided Deep
Learning Model.- 2 Deep Learning Frameworks for Histopathological Image
Processing in Colorectal Cancer Diagnostics.- 3 Improving Knee Osteoarthritis
Detection through a Multitask Learning Method from 2D MRI Slices.- 4
Enhancing Diagnostic Accuracy in Fracture Identification on Musculoskeletal
Radiographs Using Deep Learning: A Multi-Reader Retrospective Study, etc.