Computer-assisted approach to anemic erythrocyte classification using blood pathological information

Pathological blood test is one of the most important key issues in medical field prior to disease diagnosis. The aim of this paper is to design and develop a standalone application for the purpose of both acquisition and management of patient blood pathological information and generate automated anemia diagnosis report using computer vision approach. The developed system can be deployed in any pathological laboratory to help pathologist by giving support of automated anemia diagnosis and computerized report generation. Advanced image processing algorithm and data mining approach have been used to analysis patient medical information. The pathological data analysis module can process the blood test result to detect anemia type in blood. The image analysis module can identify the abnormal erythrocytes in the smear images using shape based classification. A total number of 38 shape features are extracted from each erythrocyte. Moreover, the supervised decision tree classifier C4.5 is used to classify image samples with sensitivity of 98.1% and specificity of 99.6%. The proposed system will record patient medical information like clinical data, blood test data, and microscopic smear images. Java swing, ImageJ, Weka, Java cryptography extension etc. libraries have been used to develop different applications module of the proposed system.