--- license: cc-by-4.0 task_categories: - robotics - reinforcement-learning configs: - config_name: default data_files: - split: train path: data/*/train-* dataset_info: features: - name: video_id dtype: string - name: frame_n dtype: int64 - name: timestamp dtype: float64 - name: frame_left dtype: image - name: frame_right dtype: image - name: /ECM/custom/local/setpoint_cp sequence: float64 - name: /ECM/custom/setpoint_cp sequence: float64 - name: /ECM/measured_js sequence: float64 - name: /MTML/gripper/measured_js sequence: float64 - name: /MTML/local/measured_cp sequence: float64 - name: /MTML/measured_cp sequence: float64 - name: /MTML/measured_js sequence: float64 - name: /MTMR/gripper/measured_js sequence: float64 - name: /MTMR/local/measured_cp sequence: float64 - name: /MTMR/measured_cp sequence: float64 - name: /MTMR/measured_js sequence: float64 - name: /PSM1/custom/local/setpoint_cp sequence: float64 - name: /PSM1/custom/setpoint_cp sequence: float64 - name: /PSM1/jaw/measured_js sequence: float64 - name: /PSM1/measured_js sequence: float64 - name: /PSM2/custom/local/setpoint_cp sequence: float64 - name: /PSM2/custom/setpoint_cp sequence: float64 - name: /PSM2/jaw/measured_js sequence: float64 - name: /PSM2/measured_js sequence: float64 - name: /pedals/camera dtype: bool - name: /pedals/clutch dtype: bool - name: /pedals/monopolar dtype: bool splits: - name: train num_bytes: 78489990786 num_examples: 755891 shard_lengths: [4776, 5475, 5707, 5032, 4032, 3700, 5077, 4546, 4046, 3546, 3692, 3100, 3046, 3445, 3945, 3345, 2945, 3045, 3045, 4545, 5104, 4202, 3902, 3702, 3302, 3200, 3902, 4493, 4091, 3190, 3190, 2990, 3000, 3580, 3890, 3890, 3490, 3490, 4290, 5362, 4262, 4362, 3962, 4062, 3961, 4061, 3861, 3661, 4061, 4161, 3861, 4261, 4635, 4417, 3917, 4134, 3517, 3317, 3017, 3217, 3017, 3117, 2917, 2900, 2717, 2617, 3317, 3217, 9718, 9601, 7901, 8901, 11700, 11758, 12358, 6168, 4211, 3611, 3610, 4910, 3610, 3010, 3310, 4110, 4710, 3210, 3210, 4010, 5138, 4638, 3438, 3238, 4843, 5142, 5042, 4442, 3642, 4142, 6698, 5956, 4756, 4156, 4456, 5456, 4956, 4956, 4456, 4956, 6549, 6493, 5993, 4693, 4893, 5193, 5093, 4593, 3893, 4093, 3493, 3400, 6548, 6956, 6456, 6956, 6656, 5856, 5856, 5055, 5911, 5211, 5411, 5221, 5210, 5710, 4010, 4900, 7360, 5350, 6650, 6550, 6050, 6350, 7050, 5950, 6250, 5650, 6950, 4750, 7149, 7618, 8217, 7917, 7517, 6117, 6517, 2617] --- # Comprehensive Robotic Cholecystectomy Dataset (CRCD) The **Comprehensive Robotic Cholecystectomy Dataset (CRCD)** is a large-scale, multimodal dataset for **robot-assisted surgery (RAS)** research. It provides synchronized **endoscopic videos, da Vinci surgical robot kinematics, and pedal usage signals**, making it one of the most comprehensive open datasets for studying **robotic cholecystectomy procedures**. CRCD supports research in: - Medical robotics and surgical automation - Computer vision for endoscopic surgery - Surgical workflow analysis and phase recognition - Instrument tracking and tissue segmentation - AI and machine learning in healthcare --- ## Updates - Sep 30, 2025: Corrected video timestamps for improved synchronization and cleaned up the dataset for easier use. --- ## Dataset Info - **Curated by:** Ki-Hwan Oh, Leonardo Borgioli, Alberto Mangano, Valentina Valle, Marco Di Pangrazio, Francesco Toti, Gioia Pozza, Luciano Ambrosini, Alvaro Ducas, Miloš Žefran, Liaohai Chen, Pier Cristoforo Giulianotti --- ## Dataset Sources

GitHub
Journal (Expanded)
Conference Paper
- **Raw Dataset:** Endoscopic videos, da Vinci kinematics, and console pedal usage ([link](https://uofi.box.com/s/p3aocj6yzq4ctwc0s635a2dfyk9zdv5j)) - **Annotated Dataset:** Frames with annotated **tissue segmentation** and **instrument keypoints** ([link](https://uofi.box.com/s/f9bg69ve6fkwktr3o33ahmp620w8jth6)) - **Additional Information:** Stereo endoscopic camera calibration and surgeon background data ([link](https://uofi.box.com/s/w65rui5ylm0i4v4jvlkpacpi4q6jkdpe)) --- ## Dataset Creation CRCD was collected during **robotic cholecystectomy procedures** performed on the **da Vinci surgical system**. Each case includes: - **High-resolution endoscopic video** - **Robot kinematic data** (ECM, MTML, MTMR, PSM1, PSM2) - **Surgeon pedal signals** (clutch, camera, monopolar, bipolar) Several surgeons with different levels of expertise participated, enabling research on **skill assessment, workflow modeling, and training.** --- ### License This dataset is licensed under the **Creative Commons Attribution 4.0 International License**. --- ## Citation If you use CRCD, please cite: ```bibtex @INPROCEEDINGS{oh2024crcd, author={Oh, Ki-Hwan and Borgioli, Leonardo and Mangano, Alberto and Valle, Valentina and Di Pangrazio, Marco and Toti, Francesco and Pozza, Gioia and Ambrosini, Luciano and Ducas, Alvaro and Žefran, Miloš and Chen, Liaohai and Giulianotti, Pier Cristoforo}, booktitle={2024 International Symposium on Medical Robotics (ISMR)}, title={Comprehensive Robotic Cholecystectomy Dataset (CRCD): Integrating Kinematics, Pedal Signals, and Endoscopic Videos}, year={2024}, pages={1-7}, doi={10.1109/ISMR63436.2024.10585836} } @article{oh2024crcdexpanded, author = {Oh, Ki-Hwan and Borgioli, Leonardo and Mangano, Alberto and Valle, Valentina and Pangrazio, Marco Di and Toti, Francesco and Pozza, Gioia and Ambrosini, Luciano and Ducas, Alvaro and Žefran, Miloš and Chen, Liaohai and Giulianotti, Pier Cristoforo}, title = {Expanded Comprehensive Robotic Cholecystectomy Dataset}, journal = {Journal of Medical Robotics Research}, doi = {10.1142/S2424905X25500060}, URL = {https://doi.org/10.1142/S2424905X25500060} }