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Measure the Effectiveness of an Innovative Scheme for Medical Imaging
Author(s) -
Anamika Ahirwar
Publication year - 2012
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/4577-6492
Subject(s) - computer science , measure (data warehouse) , scheme (mathematics) , medical physics , data science , data mining , medicine , mathematics , mathematical analysis
Automatic segmentation of tumor (cancer) region in medical imaging is an extremely challenging task. This plays a significant role in cancer research and clinical practices. The segmentation technique is widely used by the radiologists to segment the input medical image into meaningful regions. In this research, an innovative method is proposed for segmenting medical images based on SOM neural network. Then associate semantics to these regions using fuzzy reasoning. A hypothesis is established for brain MRI images and mammographs for breast cancer. This paper divides into seven sections: First section illustrates a brief introduction about the paper. Second section describes the overview of the scheme. Third section illustrates the image pre-processing of medical diagnosis. Computation of statistical features is described in section fourth. Section fifth calculates Chi-Square values for brain MRI images and mammogram images. Scheme evaluation for brain MRI and mammogram image are described in sixth section. Finally conclude in section seven.

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