PitVis 2023 Dataset
Overview
The PitVis 2023 is the first public dataset containing both step and instrument annotations of the endoscopic TransSphenoidal Approach (eTSA).
The dataset includes 25-videos (video_{video_number}.mp4) and the corresponding step and instrument annotation (annotations_{video_number}.csv).
Annotation metadata mapping the numerical value to its formal description is provided (map_steps.csv and map_instrument.csv), as well as video medadata (video_encoder_details.txt).
Helpful scripts and baseline models can be found on: https://github.com/dreets/pitvis.
This dataset is released as part of the PitVis Challenge, a sub-challenge of the EndoVis Challenge hosted at the annual MICCAI Conference 2024 (Vancouver, Canada on 06-Oct-2024).
- Github: https://github.com/dreets/pitvis
- Related Paper: https://arxiv.org/abs/2409.01184
Dataset
How to Load the Data
You can access the data by:
from datasets import load_dataset
datasets = load_dataset("UCL-WEISS/PitVis-2023")
Steps Map
The mapping of the surgical steps to their annotations from map_steps.csv are reproduced here for your convenience:
| Step | Description | Note |
|------|-----------------------------|------------------------------------|
| -1 | operation_not_started | |
| -1 | operation_ended | |
| -1 | out_of_patient | |
| 1 | nasal_corridor_creation | |
| 2 | anterior_sphenoidotomy | |
| 3 | septum_displacement | |
| 4 | sphenoid_sinus_clearance | |
| 5 | sellotomy | |
| 6 | durotomy | |
| 7 | tumour_excision | |
| 8 | haemostasis | |
| 9 | synthetic_graft_placement | |
| 10 | fat_graft_placement | |
| 11 | gasket_seal_construct | removed due to insufficient volume |
| 12 | dural_sealant | |
| 13 | nasal_packing | removed due to insufficient volume |
| 14 | debris_clearance | |
Instruments Map
Similarly, instrument mappings from map_instrument.csv can be found below:
| Step | Description |
|------|---------------------------------|
| -2 | no_secondary_instrument |
| -1 | out_of_patient |
| 0 | no_visible_instrument |
| 0 | occluded_image_inside_patient |
| 1 | bipolar_forceps |
| 2 | cottle |
| 3 | cup_forceps |
| 4 | dural_scissors |
| 5 | freer_elevator |
| 6 | haemostatic_foam |
| 7 | irrigation_syringe |
| 8 | kerrisons |
| 9 | micro_doppler |
| 10 | nasal_cutting_forceps |
| 11 | pituitary_rongeurs |
| 12 | retractable_knife |
| 13 | ring_curette |
| 14 | spatula_dissector |
| 15 | stealth_pointer |
| 16 | suction |
| 17 | surgical_drill |
| 18 | tissue_glue |
Split
It is suggested the following training to test split be used.
| Split | Video |
|------------|---------------------------------------------------------------------------|
| Training | 02, 03, 04, 05, 06, 07, 08, 09, 10, 11, 13, 14, 15, 16, 17, 18, 19, 20, |
| | 22, 23 |
| Validation | 01, 12, 21, 24, 25 |
License
We release the dataset under the CC-By-NC-ND-4.0 license, meaning you can copy and redistribute the material in any medium or format as long as you:
- Give appropriate credit, provide a link to the license, and indicate if changes were made
- Do not use the material for commercial purposes
- Do not redistribute the modified material
Citation
@misc{das2024pitvis2023challengeworkflowrecognition,
title={PitVis-2023 Challenge: Workflow Recognition in videos of Endoscopic Pituitary Surgery},
author={Adrito Das and Danyal Z. Khan and Dimitrios Psychogyios and Yitong Zhang and John G. Hanrahan and Francisco Vasconcelos and You Pang and Zhen Chen and Jinlin Wu and Xiaoyang Zou and Guoyan Zheng and Abdul Qayyum and Moona Mazher and Imran Razzak and Tianbin Li and Jin Ye and Junjun He and Szymon Płotka and Joanna Kaleta and Amine Yamlahi and Antoine Jund and Patrick Godau and Satoshi Kondo and Satoshi Kasai and Kousuke Hirasawa and Dominik Rivoir and Alejandra Pérez and Santiago Rodriguez and Pablo Arbeláez and Danail Stoyanov and Hani J. Marcus and Sophia Bano},
year={2024},
eprint={2409.01184},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2409.01184},
}
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