Automatic breast cancer grading of histopathological images

Jean Romain Dalle; Wee Kheng Leow; Daniel Racoceanu; Adina Eunice Tutac; Thomas C. Putti

doi:10.1109/iembs.2008.4649847

Automatic breast cancer grading of histopathological images

Jean Romain Dalle, Wee Kheng Leow, Daniel Racoceanu, Adina Eunice Tutac, Thomas C. Putti

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

77 Citas (Scopus)

Resumen

Breast cancer grading of histopathological images is the standard clinical practice for the diagnosis and prognosis of breast cancer development. In a large hospital, a pathologist typically handles 100 grading cases per day, each consisting of about 2000 image frames. It is, therefore, a very tedious and time-consuming task. This paper proposes a method for automatic computer grading to assist pathologists by providing second opinions and reducing their workload. It combines the three criteria in the Nottingham scoring system using a multi-resolution approach. To our best knowledge, there is no existing work that provide complete grading according to the Nottingham criteria.

Idioma original	Inglés
Título de la publicación alojada	Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Editorial	IEEE Computer Society
Páginas	3052-3055
Número de páginas	4
ISBN (versión impresa)	9781424418152
DOI	https://doi.org/10.1109/iembs.2008.4649847
Estado	Publicada - 2008
Publicado de forma externa	Sí
Evento	30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - Vancouver, BC, Canadá Duración: 20 ago. 2008 → 25 ago. 2008

Serie de la publicación

Nombre	Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"

Conferencia

Conferencia	30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
País/Territorio	Canadá
Ciudad	Vancouver, BC
Período	20/08/08 → 25/08/08

ODS de las Naciones Unidas

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10.1109/iembs.2008.4649847

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Dalle, J. R., Leow, W. K., Racoceanu, D., Tutac, A. E., & Putti, T. C. (2008). Automatic breast cancer grading of histopathological images. En Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 (pp. 3052-3055). Artículo 4649847 (Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"). IEEE Computer Society. https://doi.org/10.1109/iembs.2008.4649847

Dalle, Jean Romain ; Leow, Wee Kheng ; Racoceanu, Daniel et al. / Automatic breast cancer grading of histopathological images. Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. IEEE Computer Society, 2008. pp. 3052-3055 (Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology").

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title = "Automatic breast cancer grading of histopathological images",

abstract = "Breast cancer grading of histopathological images is the standard clinical practice for the diagnosis and prognosis of breast cancer development. In a large hospital, a pathologist typically handles 100 grading cases per day, each consisting of about 2000 image frames. It is, therefore, a very tedious and time-consuming task. This paper proposes a method for automatic computer grading to assist pathologists by providing second opinions and reducing their workload. It combines the three criteria in the Nottingham scoring system using a multi-resolution approach. To our best knowledge, there is no existing work that provide complete grading according to the Nottingham criteria.",

author = "Dalle, {Jean Romain} and Leow, {Wee Kheng} and Daniel Racoceanu and Tutac, {Adina Eunice} and Putti, {Thomas C.}",

year = "2008",

doi = "10.1109/iembs.2008.4649847",

language = "English",

isbn = "9781424418152",

series = "Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - {"}Personalized Healthcare through Technology{"}",

publisher = "IEEE Computer Society",

pages = "3052--3055",

booktitle = "Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08",

note = "30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 ; Conference date: 20-08-2008 Through 25-08-2008",

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Dalle, JR, Leow, WK, Racoceanu, D, Tutac, AE & Putti, TC 2008, Automatic breast cancer grading of histopathological images. En Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08., 4649847, Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology", IEEE Computer Society, pp. 3052-3055, 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08, Vancouver, BC, Canadá, 20/08/08. https://doi.org/10.1109/iembs.2008.4649847

Automatic breast cancer grading of histopathological images. / Dalle, Jean Romain; Leow, Wee Kheng; Racoceanu, Daniel et al.
Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. IEEE Computer Society, 2008. p. 3052-3055 4649847 (Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology").

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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T1 - Automatic breast cancer grading of histopathological images

AU - Dalle, Jean Romain

AU - Leow, Wee Kheng

AU - Racoceanu, Daniel

AU - Tutac, Adina Eunice

AU - Putti, Thomas C.

PY - 2008

Y1 - 2008

N2 - Breast cancer grading of histopathological images is the standard clinical practice for the diagnosis and prognosis of breast cancer development. In a large hospital, a pathologist typically handles 100 grading cases per day, each consisting of about 2000 image frames. It is, therefore, a very tedious and time-consuming task. This paper proposes a method for automatic computer grading to assist pathologists by providing second opinions and reducing their workload. It combines the three criteria in the Nottingham scoring system using a multi-resolution approach. To our best knowledge, there is no existing work that provide complete grading according to the Nottingham criteria.

AB - Breast cancer grading of histopathological images is the standard clinical practice for the diagnosis and prognosis of breast cancer development. In a large hospital, a pathologist typically handles 100 grading cases per day, each consisting of about 2000 image frames. It is, therefore, a very tedious and time-consuming task. This paper proposes a method for automatic computer grading to assist pathologists by providing second opinions and reducing their workload. It combines the three criteria in the Nottingham scoring system using a multi-resolution approach. To our best knowledge, there is no existing work that provide complete grading according to the Nottingham criteria.

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U2 - 10.1109/iembs.2008.4649847

DO - 10.1109/iembs.2008.4649847

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BT - Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08

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Dalle JR, Leow WK, Racoceanu D, Tutac AE, Putti TC. Automatic breast cancer grading of histopathological images. En Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. IEEE Computer Society. 2008. p. 3052-3055. 4649847. (Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"). doi: 10.1109/iembs.2008.4649847

Automatic breast cancer grading of histopathological images

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