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Mobiusi/Surgeons-Robotic-Interaction-Scene-Classification-Dataset

Surgeons-Robotic Interaction Scene Classification Dataset The current medical industry faces challenges of insufficient precision and lack of smooth human-robot collaboration in the application of surgical robots. Existing solutions often lack high-quality training data, which limits the intelligent decision-making and operational capabilities of robots. This dataset aims to solve the recognition and judgment problems of robots in complex surgical environments by providing rich… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Surgeons-Robotic-Interaction-Scene-Classification-Dataset.

sourceHugging Facecc-by-nc-sa-4.0updated 7mo agoView on Hugging Face
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Surgeons-Robotic Interaction Scene Classification Dataset

The current medical industry faces challenges of insufficient precision and lack of smooth human-robot collaboration in the application of surgical robots. Existing solutions often lack high-quality training data, which limits the intelligent decision-making and operational capabilities of robots. This dataset aims to solve the recognition and judgment problems of robots in complex surgical environments by providing rich images of interaction scenes between surgeons and robots. Data collection uses high-resolution cameras in real surgical environments to ensure scene authenticity. Multiple rounds of annotation and expert review ensure data quality and consistency. The data storage format is JPEG, organized by time and scene to facilitate subsequent analysis and model training. The dataset contains a total of 5000 images, with a file size of approximately 1.5G. The core advantage of this dataset lies in its high annotation accuracy and consistency, with annotation accuracy exceeding 95%. Additionally, the use of new data augmentation technologies enhances the model's adaptability in different scenes, expected to increase the recognition rate of surgical robots by 20% during operations. Applying this dataset can effectively improve the intelligence level of medical robots in surgical operations to meet actual clinical needs.

Technical Specifications

FieldTypeDescription
file_namestringFile name
qualitystringResolution
scene_categorystringThe specific scene category of interaction between the surgeon and robot in the image, such as pre-surgery preparation and intraoperative collaboration.
surgeon_countintegerThe number of surgeons appearing in the image.
roboticsystemtypestringThe type of robotic system used in the image, such as the Da Vinci surgical robot.
interaction_levelstringThe level of interaction between the surgeon and robot in the image, such as high, medium, or low.
safetymeasuresvisiblebooleanWhether clear safety measures, such as protective clothing and masks, are visible in the image.
environment_typestringThe type of environment depicted in the image, such as an operating room, conference room, or laboratory.
operative_stagestringThe stage of an operation depicted in the image. This could be preoperative, intraoperative, or postoperative.

Compliance Statement

<table> <tr> <td>Authorization Type</td> <td>CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)</td> </tr> <tr> <td>Commercial Use</td> <td>Requires exclusive subscription or authorization contract (monthly or per-invocation charging)</td> </tr> <tr> <td>Privacy and Anonymization</td> <td>No PII, no real company names, simulated scenarios follow industry standards</td> </tr> <tr> <td>Compliance System</td> <td>Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs</td> </tr> </table>

Source & Contact

If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com