Automatic Detection of Malaria Infected RBCs from a Focus Stack of Bright Field Microscope Slide Images

Gopakumar, G and Swetha, M and Siva, Gorthi Sai and Subrahmanyam, G R K S (2016) Automatic Detection of Malaria Infected RBCs from a Focus Stack of Bright Field Microscope Slide Images. In: 10th Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP), DEC 18-22, 2016, Indian Inst Technol, Guwahati, INDIA.

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Abstract

Malaria is a deadly infectious disease affecting red blood cells in humans due to the protozoan of type Plasmodium. In 2015, there is an estimated death toll of 438, 000 patients out of the total 214 million malaria cases reported worldwide. Thus, building an accurate automatic system for detecting the malarial cases is beneficial and has huge medical value. This paper addresses the detection of Plasmodium Falciparum infected RBCs from Leishman's stained microscope slide images. Unlike the traditional way of examining a single focused image to detect the parasite, we make use of a focus stack of images collected using a bright field microscope. Rather than the conventional way of extracting the specific features we opt for using Convolutional Neural Network that can directly operate on images bypassing the need for hand-engineered features. We work with image patches at the suspected parasite location there by avoiding the need for cell segmentation. We experiment, report and compare the detection rate received when only a single focused image is used and when operated on the focus stack of images. Altogether the proposed novel approach results in highly accurate malaria detection.

Item Type:	Conference Proceedings
Additional Information:	Copy right for this article belongs to the ASSOC COMPUTING MACHINERY, 1515 BROADWAY, NEW YORK, NY 10036-9998 USA
Department/Centre:	Division of Physical & Mathematical Sciences > Instrumentation Appiled Physics
Date Deposited:	15 Jul 2017 07:36
Last Modified:	15 Jul 2017 07:36
URI:	http://eprints.iisc.ac.in/id/eprint/57425

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