TrackVes Dataset
Creators
- 1. Politecnico di Milano, Istituto Italiano di Tecnologia
- 2. University College London
- 3. Ospedale Niguarda Ca' Granda, Milano - AIMS Academy
- 4. Istituto Italiano di Tecnologia
- 5. Politecnico di Milano
Description
The TrackVes dataset provides to the computer assisted surgery community a dataset for the validation of soft tissue tracking algorithms.
It is composed of nine folders:
EV1:3 - 3 video sequences of ex-vivo organs (kidney and liver);
IV1:6 - 6 video sequences of in-vivo organs (real abdominal surgical scenes);
Each folder contains:
videoLeft.avi - video sequence;
GT.xml - xml file with ground truth defined as a 2D polygon around the area to be tracked, with an interframe step of 10;
Attributes.xml - xml file indicating one of the following attributes associated to each frame (with an interframe step of 10):
0 - Safety Area Visible (SAV);
1 - Partial Occlusion (PO);
2 - Safety Area Out of Field of View (OFV);
3 - Total Occlusion (TO);
4 - DEFormation (DEF);
5 - Illumination Changes (IC);
6 - Abrupt Camera Motion (ACM);
7 - Blur (BLR);
8 - Presence of Smoke (SMK).
The C++ code implementing the ground truth generation and the tracking algorithm evaluation is available on Bitbucket -
https://bitbucket.org/ververo/envisors_track/ as:
app/gt_generator
app/tracking_evaluation.
If you use this dataset, please cite:
V. Penza, X. Du, D. Stoyanov, A. Forgione, L. Mattos and E. De Momi. "Long Term Safety Area Tracking (LT-SAT) with Online Failure Detection and Recovery for Robotic Minimally Invasive Surgery", Medical Image Analysis, 2017.
For further information, please contact veronica.penza@iit.it
Files
Additional details
References
- V. Penza, X. Du, D. Stoyanov, A. Forgione, L. Mattos and E. De Momi. "Long Term Safety Area Tracking (LT-SAT) with Online Failure Detection and Recovery for Robotic Minimally Invasive Surgery", Medical Image Analysis, 2017.