The direct visual inspection of WCE video by an expert is a tiring and cost activity and it is a true bottleneck to the widespread application of this diagnostic technique. In this paper we apply the texton approach to characterize with a numeric indicator the sub-sequences of a WCE that show sharp change and that are likely to represent relevant medical details. Experiments show that the proposed fully automatic technique may safely reduce the amount of frames that need further examination of up to 70%. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Gallo, G., Granata, E., & Scarpulla, G. (2009). Sudden changes detection in WCE video. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5716 LNCS, pp. 701–710). https://doi.org/10.1007/978-3-642-04146-4_75
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