Yet Another Computer Vision Index To Datasets (YACVID) - Details

Stand: 2017-07-23 000000m 12:49:33 - Overview

ok20
Attribute Current Content New
Name (Institute + Shorttitle)M2CAI 2016 Challenge 
Description (include details on usage, files and paper references)These datasets were generated for the M2CAI challenges, a satellite event of MICCAI 2016 in Athens. Two datasets are available for two different challenges: m2cai16-workflow for the surgical workflow challenge and m2cai16-tool for the surgical tool detection challenge. Some of the videos are taken from the Cholec80 dataset. We invite the reader to go to the M2CAI challenge page for more details regarding the dataset and the results of the past challenges. In order to maintain the ranking of the methods evaluated on these datasets, please kindly send us your quantitative results along with the corresponding technical report to: m2cai2016@gmail.com.

m2cai16-workflow dataset. This dataset is the result of collaborations with the University Hospital of Strasbourg and with the Hospital Klinikum Rechts der Isar in Munich. It contains 41 laparoscopic videos of cholecystectomy procedures. To gain access to the dataset, please kindly fill the following form: m2cai16-workflow request. To see the results of various methods, please visit the following web page: m2cai16-workflow results. If you use this dataset, you are kindly requested to cite both of the following publications that led to the generation of the dataset:

A.P. Twinanda, S. Shehata, D. Mutter, J. Marescaux, M. de Mathelin, N. Padoy, EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos, IEEE Transactions on Medical Imaging (TMI), to appear (arXiv preprint), doi:10.1109/TMI.2016.2593957, 2016
R. Stauder, D. Ostler, M. Kranzfelder, S. Koller, H. Feu▀ner, N. Navab. The TUM LapChole dataset for the M2CAI 2016 workflow challenge. CoRR, vol. abs/1610.09278, 2016.
m2cai16-tool dataset. This dataset was generated through a collaboration with the University Hospital of Strasbourg. It contains 15 laparoscopic videos of cholecystectomy procedures. To gain access to the dataset, please kindly fill the following form: m2cai16-tool request. To see the results of various methods, please visit the following web page: m2cai16-tool results. If you use this dataset, you are kindly requested to cite the work that led to the generation of the dataset:

A.P. Twinanda, S. Shehata, D. Mutter, J. Marescaux, M. de Mathelin, N. Padoy, EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos, IEEE Transactions on Medical Imaging (TMI), to appear (arXiv preprint), doi:10.1109/TMI.2016.2593957, 2016 
URL Linkhttp://camma.u-strasbg.fr/datasets 
Files (#)41 
References (SKIPPED)
Category (SKIPPED) 
Tags (single words, spaced)medicine video recognition surgery workflow challenge  
Last Changed2017-07-23 
Turing (2.12+3.25=?) :-)