Images compression for medical diagnosis using neural networks
Material type:
ArticleDescription: 1 archivo (603,2 KB)Subject(s): Online resources: Summary: Images compression is a widely studied topic. Conventional situations offer variable compression ratios depending on the image in question and, in general, do not yield good results for images that are rich in tones. This work is an application o f i mages compression o f patient's computed tomographies using neural networks, which allows to carry out both compression and decompression of the images with a fixed ratio of 8:1 and a loss of 2%.
| Item type | Home library | Collection | Call number | URL | Status | Date due | Barcode | |
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Biblioteca de la Facultad de Informática | Biblioteca digital | A0588 (Browse shelf(Opens below)) | Link to resource | No corresponde |
Formato de archivo: PDF. -- Este documento es producción intelectual de la Facultad de Informática - UNLP (Colección BIPA/Biblioteca)
Images compression is a widely studied topic. Conventional situations offer variable compression ratios depending on the image in question and, in general, do not yield good results for images that are rich in tones. This work is an application o f i mages compression o f patient's computed tomographies using neural networks, which allows to carry out both compression and decompression of the images with a fixed ratio of 8:1 and a loss of 2%.
Journal of Computer Science & Technology; 1(2)