Hysteroscopy video summarization and browsing by estimating the physician's attention on video segments.

Abstract

Specialists often need to browse through libraries containing many diagnostic hysteroscopy videos searching for similar cases, or even to review the video of one particular case. Video searching and browsing can be used in many situations, like in case-based diagnosis when videos of previously diagnosed cases are compared, in case referrals, in reviewing the patient records, as well as for supporting medical research (e.g. in human reproduction). However, in terms of visual content, diagnostic hysteroscopy videos contain lots of information, but only a reduced number of frames are actually useful for diagnosis/prognosis purposes. In order to facilitate the browsing task, we propose in this paper a technique for estimating the clinical relevance of video segments in diagnostic hysteroscopies. Basically, the proposed technique associates clinical relevance with the attention attracted by a diagnostic hysteroscopy video segment during the video acquisition (i.e. during the diagnostic hysteroscopy conducted by a specialist). We show that the resulting video summary allows specialists to browse the video contents nonlinearly, while avoiding spending time on spurious visual information. In this work, we review state-of-art methods for summarizing general videos and how they apply to diagnostic hysteroscopy videos (considering their specific characteristics), and conclude that our proposed method contributes to the field with a summarization and representation method specific for video hysteroscopies. The experimental results indicate that our method tends to produce compact video summaries without discarding clinically relevant information.