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