Por favor, use este identificador para citar o enlazar este ítem:
https://hdl.handle.net/20.500.12008/43506
Cómo citar
Registro completo de metadatos
Campo DC | Valor | Lengua/Idioma |
---|---|---|
dc.contributor.author | Gómez, Alvaro | es |
dc.contributor.author | Carbajal, Guillermo | es |
dc.contributor.author | Fuentes, Magdalena | es |
dc.contributor.author | Viñoles, Carolina | es |
dc.date.accessioned | 2024-04-16T16:21:05Z | - |
dc.date.available | 2024-04-16T16:21:05Z | - |
dc.date.issued | 2017 | es |
dc.date.submitted | 20240416 | es |
dc.identifier.citation | Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2016. Lecture Notes in Computer Science(), vol 10125. Springer, Cham. https://doi.org/10.1007/978-3-319-52277-7_43 | es |
dc.identifier.uri | https://hdl.handle.net/20.500.12008/43506 | - |
dc.description | 21st Iberoamerican Congress, CIARP 2016, Lima, Peru, 8–11, nov. 2016, | es |
dc.description.abstract | Ultrasound imaging is a veterinarian standard procedure for the monitoring of ovarian structures in cattle. Recent studies, suggest that the number of antral follicles can give a cue of the future fertility of a specimen. Therefore, there has been a growing interest in counting the number of antral follicles at early stages in life. In the most typical procedure, the operator performs a trans-rectal ultrasound scan and counts the follicles on the live video that is seen in the ultrasound machine. This is a challenging task and requires highly trained experts that can reliably detect and count the follicles in a quick sweep of a few seconds. This work presents the integration of several signal processing techniques to the problem of automatically detecting follicles in ultrasound videos of bovine cattle ovaries. The approach starts from an ultrasound video that traverses the ovary from end to end. Putative follicle regions are detected on each frame with a cascade of boosted classifiers. In order to impose temporal coherence, the detections are tracked across the frames with multiple Kalman filters. The tracks are analyzed to separate follicle detections from other false detections. The method is tested on a phantom dataset of ovaries in gelatin with dissection ground truth. Results are promising and encourage further extension to in-vivo ultrasound videos. | es |
dc.language | en | es |
dc.publisher | Springer | es |
dc.relation.ispartof | Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2016. Lecture Notes in Computer Science, vol 10125. Springer, Cham. https://doi.org/10.1007/978-3-319-52277-7_43 | es |
dc.rights | Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad De La República. (Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014) | es |
dc.subject | Follicle detection | es |
dc.subject | Cascade classifier | es |
dc.subject | Multitracking | es |
dc.subject.other | Procesamiento de Señales | es |
dc.title | Detection of follicles in ultrasound videos of bovine ovaries | es |
dc.type | Ponencia | es |
dc.rights.licence | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) | es |
Aparece en las colecciones: | Publicaciones académicas y científicas - Instituto de Ingeniería Eléctrica |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | ||
---|---|---|---|---|---|
GCFV17.pdf | 2,03 MB | Adobe PDF | Visualizar/Abrir |
Este ítem está sujeto a una licencia Creative Commons Licencia Creative Commons