AI Technology in Medical Image Analysis
Language: English
Published by MDPI AG, 2026
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 91.53
Quantity: 2 available
Add to basketItem description from seller
nach der Bestellung gedruckt Neuware - Printed after ordering - This Reprint presents eleven original research papers pushing the boundaries of automated medical decision support across diverse imaging modalities, including X-rays, MRI, CT, and histopathological scans. The presented works address critical diagnostic and therapeutic challenges using state-of-the-art artificial intelligence frameworks, such as Deep Convolutional Neural Networks (DCNNs), ResNet-50, LSTM architectures, and innovative semi-supervised learning models. Key breakthroughs presented in this volume include high-accuracy multi-class breast cancer classification, age estimation from brain scans, advanced automated quality assurance systems for chest X-rays, and customized algorithmic recommendations for orthopedic care. Furthermore, contributors explore groundbreaking methods in multi-modality thalamus segmentation, hyperparameter weight-space optimization, data augmentation techniques for data-scarce domains like gastric cancer, and high-precision lung disease detection. By prioritizing clinical efficiency, diagnostic speed, and data conformity, these studies collectively offer powerful solutions to streamline workflows, mitigate radiologist burnout, and reduce healthcare resource costs. This Reprint underscores the transformative role of AI as an essential ally to clinicians, advancing toward highly accurate, early disease detection and personalized patient care worldwide.…
Seller Inventory # 9783725882670
- Title
- AI Technology in Medical Image Analysis
- Publisher
- MDPI AG
- Publication year
- 2026
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 3725882673
- ISBN 13
- 9783725882670
- Item weight
- 700 grams
- Dimensions
- 250x175x18 mm
This Reprint presents eleven original research papers pushing the boundaries of automated medical decision support across diverse imaging modalities, including X-rays, MRI, CT, and histopathological scans. The presented works address critical diagnostic and therapeutic challenges using state-of-the-art artificial intelligence frameworks, such as Deep Convolutional Neural Networks (DCNNs), ResNet-50, LSTM architectures, and innovative semi-supervised learning models. Key breakthroughs presented in this volume include high-accuracy multi-class breast cancer classification, age estimation from brain scans, advanced automated quality assurance systems for chest X-rays, and customized algorithmic recommendations for orthopedic care. Furthermore, contributors explore groundbreaking methods in multi-modality thalamus segmentation, hyperparameter weight-space optimization, data augmentation techniques for data-scarce domains like gastric cancer, and high-precision lung disease detection. By prioritizing clinical efficiency, diagnostic speed, and data conformity, these studies collectively offer powerful solutions to streamline workflows, mitigate radiologist burnout, and reduce healthcare resource costs. This Reprint underscores the transformative role of AI as an essential ally to clinicians, advancing toward highly accurate, early disease detection and personalized patient care worldwide.
"Synopsis" may belong to another edition of this title.
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