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Pavan, M. and Pelillo, M. (2005) Efficient out-of-sample extension of dominant-set clusters. Advances in Neural Information Processing Systems, 17, 1057-1064.

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• TITLE: Automated neurosurgical video segmentation and retrieval system

  AUTHORS: Engin Mendi, Songul Cecen, Emre Ermisoglu, Coskun Bayrak

  KEYWORDS: Video Processing; Video Summarization; Video Segmentation; Image Retrieval; Image Quality Assessment

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.3 No.6, June 25, 2010

  ABSTRACT: Medical video repositories play important roles for many health-related issues such as medical imaging, medical research and education, medical diagnostics and training of medical professionals. Due to the increasing availability of the digital video data, indexing, annotating and the retrieval of the information are crucial. Since performing these processes are both computationally expensive and time consuming, automated systems are needed. In this paper, we present a medical video segmentation and retrieval research initiative. We describe the key components of the system including video segmentation engine, image retrieval engine and image quality assessment module. The aim of this research is to provide an online tool for indexing, browsing and retrieving the neurosurgical videotapes. This tool will allow people to retrieve the specific information in a long video tape they are interested in instead of looking through the entire content.