cataracts-2018-train (11 files) 2.74MB
micro_1.tar 20.49GB
micro_2.tar 30.34GB
micro_3.tar 21.51GB
micro_4.tar 36.89GB
micro_5.tar 28.98GB
tray_1.tar 32.41GB
tray_2.tar 50.00GB
tray_3.tar 42.91GB
tray_4.tar 67.60GB
tray_5.tar 51.09GB
Type: Dataset
Tags: video, surgery, ophthalmology, tool detection

title= {cataracts-2018-train},
keywords= {video, surgery, ophthalmology, tool detection},
journal= {},
author= {Gwenolé Quellec and Hassan Al Hajj and Pierre-Henri Conze and Mathieu Lamard and Béatrice Cochener},
year= {},
url= {},
license= {},
abstract= {Surgical tool detection is attracting increasing attention from the medical image processing community. The goal generally is not to precisely locate tools in images, but rather to indicate which tools are being used by the surgeon at each instant. The main motivation for annotating tool usage is to design efficient solutions for surgical workflow analysis, with potential applications in report generation, surgical training and real-time decision support.
In 2017, we organized a challenge on surgical tool detection in cataract surgery videos. With 14 participating teams, that first edition of CATARACTS was a success. Therefore, we decided to repeat this experience in 2018 with new data and new technical challenges. In particular, the 2018 edition provides two synchronized video streams per surgery: one showing the patient's eye (like in the 2017 edition), the other one showing the surgical tray. By knowing which tools exit or enter the surgical tray, we know which tools are likely being used by the surgeon and which tools surely are not. This second edition of CATARACTS is organized as a sub-challenge of the MICCAI 2018 EndoVis challenge. It should be noted that CATARACTS does not rely on endoscopic videos, but rather on microscopic videos. However, these two modalities share many similarities that justify a joint event.},
superseded= {},
terms= {see}

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