surgical-data-science

There are 10 repositories under surgical-data-science topic.

  • CAMMA-public/cholect50

    A repository for surgical action triplet dataset. Data are videos of laparoscopic cholecystectomy that have been annotated with <instrument, verb, target> labels for every surgical fine-grained activity.

    Language:Python444104

  • CAMMA-public/SelfSupSurg

    Official repository for "Dissecting Self-Supervised Learning Methods for Surgical Computer Vision"

    Language:Python337910

  • CAMMA-public/SSG-VQA

    SSG-VQA is a Visual Question Answering (VQA) dataset on laparoscopic videos providing diverse, geometrically grounded, unbiased and surgical action-oriented queries generated using scene graphs.

    Language:Python29441

  • maxboels/Surgical-Phase-Recognition

    Collated a list of useful open-access work related to surgical phase recognition and surgical skills and workflow analysis.

    19201

  • ziyiwangx/AutoLaparo

    [MICCAI'22] AutoLaparo: A New Dataset of Integrated Multi-tasks for Image-guided Surgical Automation in Laparoscopic Hysterectomy

    Language:Python14120

  • Cardio-AI/endovis-ml

    Visualization of dataset splits for surgical phase and instrument recognition

    Language:TypeScript7210

  • WuJunde/Awesome-Surgical-AI

    A curated list of surgical AI resources (continually updated)

    6300

  • CAMMA-public/cvs_annotator

    Application for reviewing and annotating frames with critical view of safety (CVS) criteria and other relevant information

    Language:Python2422

  • iTerner/Surgical-Gesture-Recognition

    Surgical Gesture Recognition Using Multi-Encoder Based Architecture.

    Language:Python2200

  • amibeuret/fastrl

    FASTRL is a a set of benchmark tasks used in surgical training which are adapted to the reinforcement learning setting for the purpose of training agents capable of providing assistance to the surgical trainees. The benchmark is provided with the purpose of exploring the domain of human-centric teaching agents within the learning-to-teach formalism

    Language:Python1100