Please use this identifier to cite or link to this item: http://dspace.sctimst.ac.in/jspui/handle/123456789/10684
Title: Volumetric Segmentation of Brain Tumor Based on Intensity Features of Multimodality Magnetic Resonance Imaging
Authors: Gupta, M
Rao, BVVSNP
Rajagopalan, V
Das, A
Kesavadas, C
Keywords: Automation & Control Systems; Computer Science; Engineering
Issue Date: 2015
Publisher: 2015 INTERNATIONAL CONFERENCE ON COMPUTER, COMMUNICATION AND CONTROL (IC4)
Citation: ,;-
Abstract: Brain tumor segmentation is a very difficult task due to vast diversity in appearance of tumor tissues among different patients and huge variations in their size and shape. In this paper, we proposed an approach which focuses on volumetric segmentation of brain tumor in three dimensions using multiple modalities of MRI brain volume including T1-weighted, T2-weighted and T1-contrast enhanced data set. Since these modalities have different contrasts for same tissue type we combined them to develop a robust segmentation approach. Qualitative and quantitative assessment of our segmentation algorithm was performed which demonstrates that proposed algorithm performs well in comparison with ground truth and other state of art methods. Proposed work provides 3D visualization of segmented tumor volume which can assist the doctors and radiologist in the diagnosis of brain tumor, as it gives information about tumor location and its features.
URI: http://dspace.sctimst.ac.in/jspui/handle/123456789/10684
Appears in Collections:Journal Articles

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