Name: Isbi 2019 C-Nmc Challenge: Classification in Cancer Cell Imaging: Select Proceedings (en Inglés)
Price: 191060.00 CLP
Availability: InStock
Author: Gupta, Anubha ; Gupta, Ritu
ISBN: 9789811508004

portada Isbi 2019 C-Nmc Challenge: Classification in Cancer Cell Imaging: Select Proceedings (en Inglés)

Formato

Libro Físico

Editorial

Springer

Autor

Gupta, Anubha ; Gupta, Ritu

Idioma

Inglés

N° páginas

147

Encuadernación

Tapa Blanda

Dimensiones

23.4 x 15.6 x 0.9 cm

Peso

0.23 kg.

ISBN13

9789811508004

Categorías

Oncología
Ingeniería: general
Ingeniería electrónica

Isbi 2019 C-Nmc Challenge: Classification in Cancer Cell Imaging: Select Proceedings (en Inglés)

Gupta, Anubha ; Gupta, Ritu (Autor) · Springer · Tapa Blanda

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Origen: Estados Unidos (Costos de importación incluídos en el precio)

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Reseña del libro "Isbi 2019 C-Nmc Challenge: Classification in Cancer Cell Imaging: Select Proceedings (en Inglés)"

This book comprises select peer-reviewed proceedings of the medical challenge - C-NMC challenge: Classification of normal versus malignant cells in B-ALL white blood cancer microscopic images. The challenge was run as part of the IEEE International Symposium on Biomedical Imaging (IEEE ISBI) 2019 held at Venice, Italy in April 2019. Cell classification via image processing has recently gained interest from the point of view of building computer-assisted diagnostic tools for blood disorders such as leukaemia. In order to arrive at a conclusive decision on disease diagnosis and degree of progression, it is very important to identify malignant cells with high accuracy. Computer-assisted tools can be very helpful in automating the process of cell segmentation and identification because morphologically both cell types appear similar. This particular challenge was run on a curated data set of more than 14000 cell images of very high quality. More than 200 international teams participated in the challenge. This book covers various solutions using machine learning and deep learning approaches. The book will prove useful for academics, researchers, and professionals interested in building low-cost automated diagnostic tools for cancer diagnosis and treatment.