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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Fully Automated Brain Tumor Segmentation Using Two MRI Modalities
verfasst von : Mohamed Ben Salah, Idanis Diaz, Russell Greiner, Pierre Boulanger, Bret Hoehn, Albert Murtha
Erschienen in: Advances in Visual Computing
Verlag: Springer Berlin Heidelberg
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An algorithm is presented for fully automated brain tumor segmentation from only two magnetic resonance image modalities. The technique is based on three steps: (1) alternating different levels of automatic histogram-based multi-thresholding step, (2) performing an effective and fully automated procedure for skull-stripping by evolving deformable contours, and (3) segmenting both Gross Tumor Volume and edema. The method is tested using 19 hand-segmented real tumors which shows very accurate results in comparison to a very recent method (STS) in terms of the Dice coefficient. Improvements of 5% and 20% respectively for segmentation of edema and Gross Tumor Volume have been recorded.