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| Acceso al texto completo restringido a Biblioteca INIA Tacuarembó. Por información adicional contacte bibliotb@tb.inia.org.uy. |
Registro completo
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Biblioteca (s) : |
INIA Tacuarembó. |
Fecha : |
14/03/2017 |
Actualizado : |
05/06/2018 |
Tipo de producción científica : |
Capítulo en Libro Técnico-Científico |
Autor : |
GÓMEZ, A.; CARBAJAL, G.; FUENTES, M.; VIÑOLES, C. |
Afiliación : |
ÁLVARO GÓMEZ; GUILLERMO CARBAJAL; MAGDALENA FUENTES; CAROLINA VIÑOLES GIL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Detection of follicles in ultrasound videos of bovine ovaries. |
Fecha de publicación : |
2017 |
Fuente / Imprenta : |
In: Beltrán-Castañón C.; Nyström I.; Famili F. (eds.). Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2016. Lecture Notes in Computer Science, vol 10125. Springer, Cham, 2017. |
Páginas : |
p. 352-359 |
DOI : |
10.1007/978-3-319-52277-7_43 |
Idioma : |
Inglés |
Contenido : |
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.
© Springer International Publishing AG 2017. |
Palabras claves : |
CASCADE CLASSIFIER; FOLLICLE DETECTION; MULTITRACKING. |
Thesagro : |
ECOGRAFIA; ULTRASONIDO. |
Asunto categoría : |
L53 Fisiología Animal - Reproducción |
Marc : |
LEADER 02272naa a2200241 a 4500 001 1056832 005 2018-06-05 008 2017 bl uuuu u00u1 u #d 024 7 $a10.1007/978-3-319-52277-7_43$2DOI 100 1 $aGÓMEZ, A. 245 $aDetection of follicles in ultrasound videos of bovine ovaries.$h[electronic resource] 260 $c2017 300 $ap. 352-359 520 $aUltrasound 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. © Springer International Publishing AG 2017. 650 $aECOGRAFIA 650 $aULTRASONIDO 653 $aCASCADE CLASSIFIER 653 $aFOLLICLE DETECTION 653 $aMULTITRACKING 700 1 $aCARBAJAL, G. 700 1 $aFUENTES, M. 700 1 $aVIÑOLES, C. 773 $tIn: Beltrán-Castañón C.; Nyström I.; Famili F. (eds.). Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2016. Lecture Notes in Computer Science, vol 10125. Springer, Cham, 2017.
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INIA Tacuarembó (TBO) |
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| Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha actual : |
21/02/2014 |
Actualizado : |
22/03/2021 |
Tipo de producción científica : |
Tesis |
Autor : |
CABRERA, D. |
Afiliación : |
CARLOS DANILO CABRERA BOLOGNA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Maturation and ripening of "Doyenne du comice" pears. [Thesis Master of Applied Science - M. Appl. Sc.] |
Fecha de publicación : |
1998 |
Fuente / Imprenta : |
Palmerston North (New Zealand): Massey University, 1998. |
Páginas : |
103 p. |
Idioma : |
Inglés |
Notas : |
A thesis presented in partial fulfilment of the requirements for the degree of Master of Applied Science in Horticultural Science at Massey University, Palmerston North, New Zealand. |
Contenido : |
ABSTRACT.
Characterisation of fruit quality attributes before and at harvest, during coolstorage and during ripening was made using standard and new, non-destructive devices during both the 1996 and 1997 seasons. Fruit firmness was linearly related to time when measured either by 'Kiwifirm' or penetrometer before harvest. Destructive techniques, the penetrometer and the texture analyser, were used to measure firmness and compared with non-destructive devices, the Kiwifirm and the softness meter. It is suggested that expressing rates of softening will be much more straightforward using a device such as the Kiwifirm. This device and the softness meter provided firmness data for pears that were too soft to measure by penetrometer. The effects of harvest date (1,11 and 21 March, 1996) and three crop loads on fruit maturity after a period of 6 weeks in coolstorage were investigated. Fruit size increased considerably during the 20 days before harvest, suggesting that periodical harvests need to be made in order to pick optimum size fruit each time. Maturity at harvest influenced the quality of 'Comice' stored at 0°C in air. Fruit from different harvests behaved differently in terms of softening behaviour and colour changes after 6 weeks in coolstorage. Crop load did not affect fruit quality attributes assessed after coolstorage. The characterisation of the nature and degree of within-tree and between tree fruit variability in harvest maturity and final ripening behaviour of 'Doyenne du Comice' pear was assessed by measuring firmness and colour. These attributes were measured non-destructively on fruit from different positions on the trees, and subsequently measured at harvest and during ripening at 20°C after 7 weeks in coolstorage at 0°C in air. Fruit behaved differently in terms of softening behaviour and colour changes depending on their position on the tree. Fruit maturity was delayed when fruit came from shaded areas, fruit from inner locations were greener than fruit from the outside and top positions. Selective picking and the association of harvest and ripening data may be important in making predictions that could reduce variability in fruit quality in the market place. MenosABSTRACT.
Characterisation of fruit quality attributes before and at harvest, during coolstorage and during ripening was made using standard and new, non-destructive devices during both the 1996 and 1997 seasons. Fruit firmness was linearly related to time when measured either by 'Kiwifirm' or penetrometer before harvest. Destructive techniques, the penetrometer and the texture analyser, were used to measure firmness and compared with non-destructive devices, the Kiwifirm and the softness meter. It is suggested that expressing rates of softening will be much more straightforward using a device such as the Kiwifirm. This device and the softness meter provided firmness data for pears that were too soft to measure by penetrometer. The effects of harvest date (1,11 and 21 March, 1996) and three crop loads on fruit maturity after a period of 6 weeks in coolstorage were investigated. Fruit size increased considerably during the 20 days before harvest, suggesting that periodical harvests need to be made in order to pick optimum size fruit each time. Maturity at harvest influenced the quality of 'Comice' stored at 0°C in air. Fruit from different harvests behaved differently in terms of softening behaviour and colour changes after 6 weeks in coolstorage. Crop load did not affect fruit quality attributes assessed after coolstorage. The characterisation of the nature and degree of within-tree and between tree fruit variability in harvest maturity and final ripening behaviour of 'Doyen... Presentar Todo |
Palabras claves : |
HARVESTING; PEARS; STORAGE; THESIS. |
Thesagro : |
ALMACENAMIENTO EN FRIO; FISIOLOGIA POSTCOSECHA; MADURAMIENTO; PERA; VARIEDADES. |
Asunto categoría : |
F01 Cultivo |
Marc : |
LEADER 03047nam a2200241 a 4500 001 1001478 005 2021-03-22 008 1998 bl uuuu m 00u1 u #d 100 1 $aCABRERA, D. 245 $aMaturation and ripening of "Doyenne du comice" pears. [Thesis Master of Applied Science - M. Appl. Sc.] 260 $aPalmerston North (New Zealand): Massey University$c1998 300 $a103 p. 500 $aA thesis presented in partial fulfilment of the requirements for the degree of Master of Applied Science in Horticultural Science at Massey University, Palmerston North, New Zealand. 520 $aABSTRACT. Characterisation of fruit quality attributes before and at harvest, during coolstorage and during ripening was made using standard and new, non-destructive devices during both the 1996 and 1997 seasons. Fruit firmness was linearly related to time when measured either by 'Kiwifirm' or penetrometer before harvest. Destructive techniques, the penetrometer and the texture analyser, were used to measure firmness and compared with non-destructive devices, the Kiwifirm and the softness meter. It is suggested that expressing rates of softening will be much more straightforward using a device such as the Kiwifirm. This device and the softness meter provided firmness data for pears that were too soft to measure by penetrometer. The effects of harvest date (1,11 and 21 March, 1996) and three crop loads on fruit maturity after a period of 6 weeks in coolstorage were investigated. Fruit size increased considerably during the 20 days before harvest, suggesting that periodical harvests need to be made in order to pick optimum size fruit each time. Maturity at harvest influenced the quality of 'Comice' stored at 0°C in air. Fruit from different harvests behaved differently in terms of softening behaviour and colour changes after 6 weeks in coolstorage. Crop load did not affect fruit quality attributes assessed after coolstorage. The characterisation of the nature and degree of within-tree and between tree fruit variability in harvest maturity and final ripening behaviour of 'Doyenne du Comice' pear was assessed by measuring firmness and colour. These attributes were measured non-destructively on fruit from different positions on the trees, and subsequently measured at harvest and during ripening at 20°C after 7 weeks in coolstorage at 0°C in air. Fruit behaved differently in terms of softening behaviour and colour changes depending on their position on the tree. Fruit maturity was delayed when fruit came from shaded areas, fruit from inner locations were greener than fruit from the outside and top positions. Selective picking and the association of harvest and ripening data may be important in making predictions that could reduce variability in fruit quality in the market place. 650 $aALMACENAMIENTO EN FRIO 650 $aFISIOLOGIA POSTCOSECHA 650 $aMADURAMIENTO 650 $aPERA 650 $aVARIEDADES 653 $aHARVESTING 653 $aPEARS 653 $aSTORAGE 653 $aTHESIS
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