Proceedings of 2023 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2023) : Medical Imaging and Computer-Aided Diagnosis / edited by Ruidan Su, Yu-Dong Zhang, Alejandro F. Frangi

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Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Lecture Notes in Electrical Engineering ; 1166Publisher: Singapore : Springer Nature Singapore, 2024Publisher: Singapore : Imprint: Springer, 2024Edition: 1st ed. 2024Description: 1 Online-Ressource(XIV, 406 p. 171 illus., 138 illus. in color.)ISBN:

9789819713356

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Additional physical formats: 9789819713349 | 9789819713363 | 9789819713370 | Erscheint auch als: 9789819713349 Druck-Ausgabe | Erscheint auch als: 9789819713363 Druck-Ausgabe | Erscheint auch als: 9789819713370 Druck-AusgabeDOI: DOI: 10.1007/978-981-97-1335-6Online resources:

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Summary: Medical Imaging -- Computer Aided Detection/Diagnosis -- Machine learning and Deep learning -- Others.Summary: This book covers virtually all aspects of image formation in medical imaging, including systems based on ionizing radiation (x-rays, gamma rays) and non-ionizing techniques (ultrasound, optical, thermal, magnetic resonance, and magnetic particle imaging) alike. In addition, it discusses the development and application of computer-aided detection and diagnosis (CAD) systems in medical imaging. This book includes the state-of-the-art research of computer-aided diagnosis systems with aritificial intelligence. Given its coverage, the book provides both a forum and valuable resource for researchers involved in image formation, experimental methods, image performance, segmentation, pattern recognition, feature extraction, classifier design, machine learning / deep learning, radiomics, CAD workstation design, human–computer interaction, databases, and performance evaluation.PPN: PPN: 1883169526Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SCS | ZDB-2-SXCS

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