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Please use this identifier to cite or link to this item: http://hdl.handle.net/1812/62

Title: Image Acquisition and Retrieval Systems For Leukaemia Cells
Authors: Rajendran, Shobana
Keywords: Medic Informatics
Computational Intelligence
Issue Date: 2007
Abstract: Medical Informatics is the field that deals with biomedical information, data, and knowledge - their storage, retrieval, and optimal use for problem solving and decision making. Medical Informatics can be realized by the application of Computational Intelligence (CI) techniques in the medical filed. CI has many abilities in data processing and structuring, pattern matching, forming knowledge base, reasoning and decision making. The aim of this project was to use CI techniques for syntactical and contextual Image retrieval for leukaemic images and for creating a knowledge base, reasoning and decision making for an expert system that would aid the clinicians in their daily routine. A logical approach was used to systematically develop content based image retrieval system that supports decision making in clinical hematopathology. The decision support system can locate, retrieve, and display cases which exhibit morphological profiles consistent to the case in question. The system uses an image database containing digitized specimens which belong to classes of lymphocytic, myelocytic and megakaryocytic disorders and a class of healthy leukocytes. The developed system is based on open source. Pages were designed and developed using Java server pages and Java with MySQL as the database for the domain and image repository. Several Java-based tools are used for image processing, neural network based pattern classification and recognition, and for the hybrid system, that is, rule and model based reasoning expert system. The classification rates for individual white blood cells varied between 97-98% for training data and 95-96% for testing data depending on the individual cell type- monocyte, lymphocyte, eosinophil, basophil and neutrophil.The expert system was engineered with the knowledge base of healthy individual cells with their semantic annotation and a rule based reasoning system to form a diagnostic decision support system. This research proposes a patient management system and decision support system (considering certain types of leukaemia as the domain) for the Hematology Department of Hospital Kuala Lumpur (HKL), Malaysia.
Description: Master of Computer Science
URI: http://dspace.fsktm.um.edu.my/handle/1812/62
Appears in Collections:Masters Dissertations: Computer Science

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