Biomedical Image Processing and Classification

Biomedical Image Processing and Classification

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 imag...

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Detalles Bibliográficos
Otros Autores: Mesin, Luca (Editor)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Materias:
Technology: general issues
MR brain segmentation
fuzzy clustering
object extraction
silhouette analysis
DICOM processing
3D modeling
semantic segmentation
convolutional neural networks
kidney biopsy
kidney transplantation
glomerulus detection
glomerulosclerosis
pattern recognition
hemoglobin
anemia
human tissues
conjunctiva
non-invasive medical device
training size
deep learning
convolutional neural network
U-Net
segmentation
artificial intelligence
digital pathology
kidney fibrosis
blood vessel segmentation
inferior vena cava
ultrasound imaging
binary tree model
pulsatility
fluid volume assessment
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009654373606719
Descripción
Sumario: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.
Descripción Física:1 electronic resource (116 p.)
Acceso:Open access

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