Medical Imaging and Computer-Aided Diagnosis : Proceeding of 2020 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2020) / edited by Ruidan Su, Han Liu
Contributor(s): Su, Ruidan, editor literario
| Liu, Han, editor literario
Material type:
E-bookSeries: (Lecture Notes in Electrical Engineering, 1876-1100; 633); (Engineering (SpringerNature-11647)); (Engineering (R0) (SpringerNature-43712)).Publisher: Singapore : Springer International Publishing, 2020Edition: First edition.Description: 1 recurso en línea (XI, 244 páginas) : 107 ilustraciones, 76 ilustraciones a color.ISBN: 9789811551994.Subject: Diagnóstico por imagen -- Congresos y asambleas
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|
LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias de la Salud | RC78.7.D53 2020 EB (Browse shelf(Opens below)) | Acceso electrónico | eBook.11082032 |
Optical and Photo-acoustic Imaging -- Image Analysis and Signal Processing -- Shape Representation and Analysis -- Image Reconstruction -- Imaging and Genomics -- Image Guided Surgery -- Image-Guided Interventions and Surgery -- Segmentation -- Pattern recognition -- Feature extraction -- Classifier design -- Machine learning including deep learning -- Radiomics -- CAD workstation design -- Human-computer interaction.
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. 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.
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