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Proceedings of 2024 International Co...

International Conference on Medical Imaging and Computer-Aided Diagnosis (2024 :)

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Proceedings of 2024 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2024) = medical imaging and computer-aided diagnosis /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Proceedings of 2024 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2024)/ edited by Ruidan Su, Alejandro F. Frangi, Yudong Zhang.
Reminder of title:	medical imaging and computer-aided diagnosis /
remainder title:	MICAD 2024
other author:	Ruidan, Su.
corporate name:	International Conference on Medical Imaging and Computer-Aided Diagnosis
Published:	Singapore :Springer Nature Singapore : : 2025.,
Description:	xvi, 592 p. :ill. (chiefly color), digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Diagnostic imaging - Congresses. - Data processing -
Online resource:	https://doi.org/10.1007/978-981-96-3863-5
ISBN:	9789819638635

Proceedings of 2024 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2024) = medical imaging and computer-aided diagnosis /
Proceedings of 2024 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2024)medical imaging and computer-aided diagnosis /[electronic resource] :MICAD 2024edited by Ruidan Su, Alejandro F. Frangi, Yudong Zhang. - Singapore :Springer Nature Singapore :2025. - xvi, 592 p. :ill. (chiefly color), digital ;24 cm. - Lecture notes in electrical engineering,13721876-1119 ;. - Lecture notes in electrical engineering ;1372..

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.

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.

ISBN: 9789819638635

Standard No.: 10.1007/978-981-96-3863-5doiSubjects--Topical Terms:

893542
Diagnostic imaging
--Data processing--Congresses.

LC Class. No.: RC78.7.D53

Dewey Class. No.: 616.0754

Proceedings of 2024 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2024) = medical imaging and computer-aided diagnosis /
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505 0 $a 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.
520 $a 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.
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