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Record Nr. |
UNINA9910411936203321 |
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Titolo |
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 |
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Pubbl/distr/stampa |
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Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (XI, 244 p. 107 illus., 76 illus. in color.) |
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Collana |
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Lecture Notes in Electrical Engineering, , 1876-1100 ; ; 633 |
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Disciplina |
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Soggetti |
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Biomedical engineering |
Signal processing |
Image processing |
Speech processing systems |
Optical data processing |
Pattern recognition |
Radiology |
Biomedical Engineering and Bioengineering |
Signal, Image and Speech Processing |
Image Processing and Computer Vision |
Pattern Recognition |
Diagnostic Radiology |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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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. |
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Sommario/riassunto |
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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, |
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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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