Automatic Segmentation of Region of Interests in MR Images Using Saliency Information and Active Contours

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 215)

Abstract

Magnetic resonance imaging (MRI) is the most clinically used and gifted modality to identify brain abnormalities in individuals who might be at risk for brain cancer. To date, automated brain tumor segmentation from MRI modalities remains a sensitive, computationally expensive, and a demanding task. This paper presents an automated and robust segmentation method to enable investigators to make successful diagnosis and planning of radiosurgery by reducing the risk factor and study duration. The proposed system consists of following steps: (1) remove the non-brain part from MRI, (2) estimate saliency map of MRI, (3) use the salient region (tumor) as an identification marker and segment the salient object by finding the “optimal” closed contour around the tumor. The system has been tested on real patient images with excellent results. The qualitative and quantitative evaluations by comparing with ground truths and with other existing approaches demonstrate the effectiveness of the proposed method.

Keywords

Visual saliency MRI Tumor detection Active contours 

Notes

Acknowledgments

This research is supported by: (1) The Industrial Strategic technology development program, 10041772, (The Development of an Adaptive Mixed-Reality Space based on Interactive Architecture) funded by the MKE (Ministry of Knowledge Economy, Korea) and, (2) The Ministry of Knowledge Economy (MKE), Korea, under IT/SW Creative research program supervised by the National IT Industry Promotion Agency (NIPA)” (NIPA-2012-H0502-12-1013).

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.College of Electronics and Information EngineeringSejong UniversitySeoulRepublic of Korea
  2. 2.College of BusinessHonam UniversityGwangjuRepublic of Korea

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