Classification of normal versus malignant cells in B-ALL white blood cancer microscopic images

Honnalgere, A and Nayak, G (2019) Classification of normal versus malignant cells in B-ALL white blood cancer microscopic images. [Book Chapter]

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Abstract

Identification of malignant cells is an important aspect of cancer diagnosis and in determining the degree of progression. Blood disorders, such as leukemia, are most often detected only in advanced stages, when the number of cancer cells is much higher than the number of normal cells. Differentiation of cancer cells from normal blood cells is challenging due to their acute morphological similarity. Early diagnosis of leukemia relies on the accurate classification of malignant cells versus normal cells in microscopic images of blood cells. Computer-aided cell classification has gained popularity as an efficient technique for the diagnosis of leukemia. Our approach to classification involves finetuning of a VGG16 neural network with batch normalization to classify the images of malignant vis-Ã -vis normal cells.

Item Type:	Book Chapter
Publication:	Lecture Notes in Bioengineering
Publisher:	Springer
Additional Information:	The copyright for this article belongs to Springer.
Keywords:	Transfer learning; VGG16
Department/Centre:	Division of Interdisciplinary Sciences > Computational and Data Sciences
Date Deposited:	05 Dec 2022 05:59
Last Modified:	05 Dec 2022 05:59
URI:	https://eprints.iisc.ac.in/id/eprint/78210

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