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TUMOR DETECTION IN MRI AND MAMMOGRAM IMAGES USING STATISTICAL TEXTURE ANALYSIS AND FEATURE EXTRACTION

International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

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Abstract

Tumour images obtained are used for further diagnosis and prediction pertaining to type of tumor. Medical images are used to diagnosis the possibility of diagnosis. However, there is a higher possibility of false detection of the images as the manual and personal knowledge of the expert is involved in this. Digital Images obtained are analyzed based on the statistical features and characteristics. Digitized images for further diagnosis in case of suspected Brain tumor. MRI technique is used to obtain these 2D images of Brain map. In case of Breast tumor diagnosis, the technique used is Mammography. These images are in digital form and in two dimensional in nature. Image analysis and their statistical feature abstraction is one of the important aspects in process to early detection of tumor existence, their size and type of tumor. This can be helpful in early detection and rapid follow up actions to cure the problem. This study aims to work on aspects of digital image analysis using its statistical features and how they can be used for the purpose of early detection. Datasets of images are obtained for both Brain tumor images using MRI and Breast tumor images using Mammogram. These images are in digital forms and contain noise. Using appropriate noise removal technique, the obtained datasets are used for statistical analysis using SciLab®. The feature extraction technique is used to obtain the area of interest. Statistical measurement matrices are generated for the purpose of area of interest identification. The measured features are used to verify and observe the results using blind datasets. Tumor texture and statistical analysis can be done using this to identify the similarities and difference among the obtained results of both types of tumors. The obtained results show that above 67% of blind dataset images of brain tumor and above 84% of breast tumors falls within the obtained statistical measurement matrices.

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Keywords

Brain and breast tumour, Digital Image Statistical features, Image texture analysis, Digital Image analysis, Medical Image Analysis.

Image
  • Format Volume 1, Issue 2, No 5, 2014
  • Copyright All Rights Reserved ©2013
  • Year of Publication 2013
  • Author Kavita Ahuja
  • Reference IJCS-SI-24
  • Page No 001 - 016

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