Convolutional neural network-based malaria diagnosis from focus stack of blood smear images acquired using custom-built slide scanner

Gopakumar, Gopalakrishna Pillai and Swetha, Murali and Siva, Gorthi Sai and Subrahmanyam, Gorthi R K Sai (2018) Convolutional neural network-based malaria diagnosis from focus stack of blood smear images acquired using custom-built slide scanner. In: JOURNAL OF BIOPHOTONICS, 11 (3).

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Abstract

The present paper introduces a focus stacking-based approach for automated quantitative detection of Plasmodium falciparum malaria from blood smear. For the detection, a custom designed convolutional neural network (CNN) operating on focus stack of images is used. The cell counting problem is addressed as the segmentation problem and we propose a 2-level segmentation strategy. Use of CNN operating on focus stack for the detection of malaria is first of its kind, and it not only improved the detection accuracy (both in terms of sensitivity 97.06%] and specificity 98.50%]) but also favored the processing on cell patches and avoided the need for hand-engineered features. The slide images are acquired with a custom-built portable slide scanner made from low-cost, off-the-shelf components and is suitable for point-of-care diagnostics. The proposed approach of employing sophisticated algorithmic processing together with inexpensive instrumentation can potentially benefit clinicians to enable malaria diagnosis.

Item Type:	Journal Article
Publication:	JOURNAL OF BIOPHOTONICS
Publisher:	WILEY-V C H VERLAG GMBH, POSTFACH 101161, 69451 WEINHEIM, GERMANY
Additional Information:	Copy right for the article belong toWILEY-V C H VERLAG GMBH, POSTFACH 101161, 69451 WEINHEIM, GERMANY
Department/Centre:	Division of Physical & Mathematical Sciences > Instrumentation Appiled Physics
Date Deposited:	03 Apr 2018 18:27
Last Modified:	03 Apr 2018 18:27
URI:	http://eprints.iisc.ac.in/id/eprint/59459

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