alexa Different Automatic Techniques Of Brain Tumour Detection And Segmentation
ISSN: 2155-6210

Journal of Biosensors & Bioelectronics
Open Access

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In Association with
 
romanian
 
icamb2015

3rd International Conference and Exhibition on Biosensors & Bioelectronics
August 11-13, 2014 Hilton San Antonio Airport, San Antonio, USA

Gunjan Gautam
Accepted Abstracts: J Biosens Bioelectron
DOI: 10.4172/2155-6210.S1.022
Abstract
Brain tumour segmentation plays a vital role in the emerging field of medical imaging to assist the research studies as well as for the surgical planning. The goal of the image segmentation is to remove the surroundings which are not that much important at that point of a time and to extract our region of interest (ROI) so that the lesion can be focused more. Tumour segmentation is a bit challenging task depending upon its varieties in terms of size, geometry and location. Earlier, segmentation was being done manually which was time consuming, typical and prone to be erroneous. To overcome these limitations, computer science people moved on to Automatic tools for the detection and segmentation. This article provides a comprehensive review over different detection and segmentation techniques falling in two major categories; intelligence based and non-intelligence based.
Biography
Gunjan Gautam is currently in final year of Master of Technology in Computer Science, Banasthali University, Rajasthan, India, pursuing project training from Indian Statistical Institute.
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