Biomedical Image Processing and Classification

• Autore: Mesin Luca
• Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
• Descrizione fisica: 1 online resource (116 p.)
• Soggetto topico: Technology: general issues
• Soggetto non controllato: 3D modeling; anemia; artificial intelligence; binary tree model; blood vessel segmentation; conjunctiva; convolutional neural network; convolutional neural networks; deep learning; DICOM processing; digital pathology; fluid volume assessment; fuzzy clustering; glomerulosclerosis; glomerulus detection; hemoglobin; human tissues; inferior vena cava; kidney biopsy; kidney fibrosis; kidney transplantation; MR brain segmentation; n/a; non-invasive medical device; object extraction; pattern recognition; pulsatility; segmentation; semantic segmentation; silhouette analysis; training size; U-Net; ultrasound imaging
• Persona (resp. second.): MesinLuca
• Sommario/riassunto: Biomedical image processing is an interdisciplinary field involving a variety of disciplines, e.g., electronics, computer science, physics, mathematics, physiology, and medicine. Several imaging techniques have been developed, providing many approaches to the study of the human body. Biomedical image processing is finding an increasing number of important applications in, for example, the study of the internal structure or function of an organ and the diagnosis or treatment of a disease. If associated with classification methods, it can support the development of computer-aided diagnosis (CAD) systems, which could help medical doctors in refining their clinical picture.
• Titolo autorizzato: Biomedical Image Processing and Classification
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910557339403321
• Lo trovi qui: Univ. Federico II