Image-to-Image Translation in PyTorch

Official repository of "SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory"

CycleGAN based CT-Ultrasound image-to-image translation

PyTorch implementation of 3D U-Net for kidney and tumor segmentation from KiTS19 CT scans.

Prostate cancer detection from ultrasound using foundation models and domain knowledge

Code release for NeRF (Neural Radiance Fields)

Instant neural graphics primitives: lightning fast NeRF and more

This repository contains the codes for our study involving an end-to-end deep machine learning framework developed to ‎sequentially detect ultrasound regions of interest, ‎segment kidneys from US i…

Towards ubiquitous ultrasound.

Segment Anything in Medical Images

[MICCAI2022] This is an official PyTorch implementation for A Robust Volumetric Transformer for Accurate 3D Tumor Segmentation

A 3D Slicer integration to Meta's SAM.

Python package for DICOM-SEG medical segmentation file reading and writing

Automatic Landmark Identification

A tool for precisely placing 3D landmarks on 3D facial scans based on the paper "Multi-view Consensus CNN for 3D Facial Landmark Placement"

Pytorch port for Parametric Umap

Uniform Manifold Approximation and Projection

The reference implementaiton for the paper "Deep Geometric Prior for Surface Reconstruction"

Code base of ParSeNet: ECCV 2020.

Module to compute labelmap statistics in bulk

Implementation of Firefly Algorithm in Python

A spatial aware implementation of elliptical Fourier analysis

[ICCV 2021] "HPNet: Deep Primitive Segmentation Using Hybrid Representations"

PyTorch reproduction of paper V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image

A Python package to perform topology and topology-based analyses of flow fields.

Preoperative planning framework for minimally-invasive surgery featuring image processing (with ITK, VTK and Tensorflow) and curvature constrained trajectory planning (using OMPL)

Pytorch reimplementation of the Vision Transformer (An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale)