dc.contributor | IMMUNOCAMP Pesquisa e Desenvolvimento de Tecnologia | |
dc.contributor | Universidade Estadual de Campinas (UNICAMP) | |
dc.contributor | Universidade de São Paulo (USP) | |
dc.contributor | Universidade Estadual Paulista (Unesp) | |
dc.date.accessioned | 2014-05-27T11:30:13Z | |
dc.date.accessioned | 2022-10-05T18:57:29Z | |
dc.date.available | 2014-05-27T11:30:13Z | |
dc.date.available | 2022-10-05T18:57:29Z | |
dc.date.created | 2014-05-27T11:30:13Z | |
dc.date.issued | 2013-08-22 | |
dc.identifier | Proceedings - International Symposium on Biomedical Imaging, p. 460-463. | |
dc.identifier | 1945-7928 | |
dc.identifier | 1945-8452 | |
dc.identifier | http://hdl.handle.net/11449/76314 | |
dc.identifier | 10.1109/ISBI.2013.6556511 | |
dc.identifier | 2-s2.0-84881627920 | |
dc.identifier | 9039182932747194 | |
dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/3925205 | |
dc.description.abstract | Intestinal parasitosis constitutes a serious health problem in most tropical countries. The diagnosis of enteroparasites in laboratory routine relies on the examination of stool samples using optical microscopy and the error rates usually range from moderate to high. Approaches based on automatic image analysis have been proposed, but the methods are usually specific for some species, some of them are computationally expensive, and image acquisition and focus are manual. We present a solution to automate the diagnosis of the 15 most common species of enteroparasites in Brazil, using a sensitive parasitological technique, a motorized microscope with digital camera for automatic image acquisition and focus, and fast image analysis methods. The results indicate that our solution is effective and suitable for laboratory routine, in which the exam must be concluded in a few minutes. © 2013 IEEE. | |
dc.language | eng | |
dc.relation | Proceedings - International Symposium on Biomedical Imaging | |
dc.relation | 0,426 | |
dc.rights | Acesso aberto | |
dc.source | Scopus | |
dc.subject | Automated diagnosis | |
dc.subject | image segmentation | |
dc.subject | intestinal parasitosis | |
dc.subject | microscopy image analysis | |
dc.subject | pattern recognition | |
dc.subject | Automatic image analysis | |
dc.subject | Common species | |
dc.subject | Image analysis method | |
dc.subject | Intestinal parasites | |
dc.subject | Microscopy image analysis | |
dc.subject | Tropical countries | |
dc.subject | Image acquisition | |
dc.subject | Image analysis | |
dc.subject | Image segmentation | |
dc.subject | Medical imaging | |
dc.subject | Optical microscopy | |
dc.subject | Pattern recognition | |
dc.subject | Optical data storage | |
dc.title | Automated diagnosis of human intestinal parasites using optical microscopy images | |
dc.type | Trabalho apresentado em evento | |