3D U-Net model for volumetric semantic segmentation written in pytorch
Python code to fuse multiple RGB-D images into a TSDF voxel volume.
Fuse multiple depth frames into a TSDF voxel volume.
Voxel2Mesh: 3D Mesh Model Generation from Volumetric Data
Skeletonize densely labeled 3D image segmentations with TEASAR. (Medial Axis Transform)
Read and write Neuroglancer datasets programmatically.
Analysis of 3D pathology samples using weakly supervised AI - Cell
The implementation of 3D-UNet using PyTorch
Marching Cubes & Mesh Simplification on multi-label 3D images.
ForkNet: Adversarial Semantic Scene Completion from a Single Depth Image - ICCV 2019
[MICCAI'2020 PRIME] Uniformizing Techniques to Process CT scans with 3D CNNs for Tuberculosis Severity Estimation.
Compose chunk operators to create a pipeline for local or distributed petabyte-scale computation
Scalable Neuroglancer compatible Downsampling, Meshing, Skeletonizing, Contrast Normalization, Transfers and more.
🤗 AeroPath: An airway segmentation benchmark dataset with challenging pathology
Quanfima (Quantitative Analysis of Fibrous Materials)
[MICCAI 2023] This is the official code for the paper "A Feature-Driven Richardson-Lucy Deconvolution Network"
Matlab codes to create synthetic fractures for multiphase simulation
Implementation of the Marching Cubes algorithm on Python.
Volume Data Rendering using GPU Raycasting/Raymarching
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