An Intelligent Decision Support System for Leukaemia Diagnosis using Microscopic Blood Images

Siew Chin Neoh, Worawut Srisukkham, Li Zhang, Stephen Todryk, Brigit Greystoke, Chee Peng Lim, Mohammed Alamgir Hossain, Nauman Aslam

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Abstract

This research proposes an intelligent decision support system for acute lymphoblastic leukaemia diagnosis from microscopic blood images. A novel clustering algorithm with stimulating discriminant measures (SDM) of both within- and between-cluster scatter variances is proposed to produce robust segmentation of nucleus and cytoplasm of lymphocytes/lymphoblasts. Specifically, the proposed between-cluster evaluation is formulated based on the trade-off of several between-cluster measures of well-known feature extraction methods. The SDM measures are used in conjuction with Genetic Algorithm for clustering nucleus, cytoplasm, and background regions. Subsequently, a total of eighty features consisting of shape, texture, and colour information of the nucleus and cytoplasm sub-images are extracted. A number of classifiers (multi-layer perceptron, Support Vector Machine (SVM) and Dempster-Shafer ensemble) are employed for lymphocyte/lymphoblast classification. Evaluated with the ALL-IDB2 database, the proposed SDM-based clustering overcomes the shortcomings of Fuzzy C-means which focuses purely on within-cluster scatter variance. It also outperforms Linear Discriminant Analysis and Fuzzy Compactness and Separation for nucleus-cytoplasm separation. The overall system achieves superior recognition rates of 96.72% and 96.67% accuracies using bootstrapping and 10-fold cross validation with Dempster-Shafer and SVM, respectively. The results also compare favourably with those reported in the literature, indicating the usefulness of the proposed SDM-based clustering method.

Original languageEnglish
Article number14938
JournalScientific Reports
Volume5
DOIs
Publication statusPublished - 9 Oct 2015

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Chin Neoh, S., Srisukkham, W., Zhang, L., Todryk, S., Greystoke, B., Lim, C. P., Hossain, M. A., & Aslam, N. (2015). An Intelligent Decision Support System for Leukaemia Diagnosis using Microscopic Blood Images. Scientific Reports, 5, [14938]. https://doi.org/10.1038/srep14938