Morphological Segmentation of the Brain Tumors Using LabVIEW

Automated brain tumor segmentation is a vital task in medical diagnostics as it provides location details and information related to anatomical structures of the tumor. This helps doctors to delineate abnormal tissue of tumor and to formulate appropriate surgical planning. In this work, an image analysis approach using thresholding and morphological techniques for automated segmentation of tumor from brain MRI is introduced. Morphological opening-closing operations modify the original image to eliminate the noise and small regular details while preserve the larger object contours without less location offsets. The physical dimensions of the tumor viz., location, area, which are of utmost importance to the physicians, are also found using the present technique. The segmentation techniques are implemented using graphical programming language LabVIEW with its associated tool IMAQ Vision. We have realized an automatic system as the LabVIEW software used in our system can communicate with and control other equipments used in this system. Hence our proposed system is potentially effective on diagnostic tasks that require the efficient segmentation of tumors. The results of this analysis are useable in designing a fuzzy or a neural network for more accurate analysis.