This repo contains an implementation code for the weakly supervised surgical tool tracker. In this research, the temporal dependency in surgical video data is modeled using a convolutional LSTM which is trained only on image level labels to detect, localize and track surgical instruments.

Visualization of dataset splits for surgical phase and instrument recognition

This is done as part of my sophomore research intern. It uses deep learning for surgical tool detection. It can also be used to define the quality of surgery and easily extendable provide a rating after surgery is over.

An open-source non-official community implementation of the model from the paper: Surgical Robot Transformer (SRT): Imitation Learning for Surgical Tasks: https://surgical-robot-transformer.github.io/

modular stereotaxic holder for implanting optic fibers, guide cannulas, and GRIN anchors

Micron Scale Tracking of surgical forceps using a quadcamera system

3D printed mouse stereotax

Various parts for stereotaxic surgery

Rat neonate stereotactic platform.

UnityIGTConnector is a Unity integration of the OpenIGTLink protocol, allowing for real-time communication and advanced visualization of medical data in mixed reality applications. Perfect for enhancing surgical support with HoloLens 2

Simple devices and software to facilitate microscopy, electrophysiology, and microbiology techniques for systems neuroscience research. Easy to fabricate and use with low-cost 3D Printers.

A software prototype for breast biopsy needle navigation and guidance through a augmented reality viewer