Madhumala Ghosh

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The objective of this paper is to introduce a computer assisted prediction of malaria infection particularly Plasmodium vivax based on the morphological and textural information. Here erythrocytes have been segmented from light microscopic images of peripheral blood smear using marker controlled watershed followed by pre-processing. Thereafter texture and(More)
The aim of this paper is to address the development of computer assisted malaria parasite characterization and classification using machine learning approach based on light microscopic images of peripheral blood smears. In doing this, microscopic image acquisition from stained slides, illumination correction and noise reduction, erythrocyte segmentation,(More)
This paper aims at introducing a textural pattern analysis approach to Plasmodium vivax (P. vivax) detection from Leishman stained thin blood film. This scheme follows retrospective study design protocol where patients were selected at random in the clinic. The scheme consists of four stages – artefacts reduction, fuzzy divergence-based segmentation of P.(More)
This paper aims at introducing a new approach to Plasmodium vivax (P. vivax) detection from Leishman stained thin blood film. This scheme follows retrospective study design protocol where patients were selected at random in the clinic. The scheme consists of two main stages - firstly artefacts reduction, and secondly fuzzy divergence based segmentation of(More)
This paper introduces a hedge operator based fuzzy divergence measure and its application in segmentation of leukocytes in case of chronic myelogenous leukemia using light microscopic images of peripheral blood smears. The concept of modified discrimination measure is applied to develop the measure of divergence based on Shannon exponential entropy and(More)
This paper aims at introducing an automated approach to leukocyte recognition using fuzzy divergence and modified thresholding techniques. The recognition is done through the segmentation of nuclei where Gamma, Gaussian and Cauchy type of fuzzy membership functions are studied for the image pixels. It is in fact found that Cauchy leads better segmentation(More)
The paper provides a novel approach to represent cooperative/competitive interactions among coexisting emotions by a recurrent neural dynamics, and proposes a scheme for parameter estimation of the dynamics from the facial expressions of the subjects, psychologically excited by audio-visual stimulus taken from select commercial movies. Conditions for(More)
Quantitative microscopy has strengthened conventional diagnostic scheme through better understanding of microscopic features from clinical perspective. Towards this, pathological image analysis has gained immense significance among medical fraternity through visualization and quantitative evaluation of clinical features. Till today pathological inspection(More)
The paper proposes a robust approach to automatic segmentation of leukocyte's nucleus from microscopic blood smear images under normal as well as noisy environment by employing a new exponential intuitionistic fuzzy divergence based thresholding technique. The algorithm minimizes the divergence between the actual image and the ideally thresholded image to(More)
The paper presents an analysis of chaos, limit cycles and stability in the antigen-antibody interactive dynamics. Both cooperation and competition of antibodies are considered in the dynamics. The classical approach of Lyapunov has been employed here for the stability analysis of the dynamics. Computer simulations have been undertaken to support the results(More)