Diagnosis is the first step before giving a medicine to the patient. In the recent past such diagnosis is performed using medical images where segmentation is the prime part in the medical image retrieval which improves the feature set that is collected from the segmented image. In this paper, it is proposed to segment the medical image a semi decision algorithm that can segment only the tumor part from the CT image. Further texture based techniques are used to extract the feature vector from the segmented region of interest. Medical images under test are classified using decision tree classifier. Results show better performance in terms of accuracy when compared to the conventional methods.
CITATION STYLE
. V. V. S. T. (2015). A NOVEL MEDICAL IMAGE SEGMENTATION AND CLASSIFICATION USING COMBINED FEATURE SET AND DECISION TREE CLASSIFIER. International Journal of Research in Engineering and Technology, 04(09), 83–86. https://doi.org/10.15623/ijret.2015.0409014
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