一个命令行工具,可以将DICOM体积转换为3D表面网格(obj、stl 或 ply)。可以启用多种网格处理程序,如网格简化、平滑或清洁。支持Linux、OSX和Windows。
ct-scans 开源项目推荐(103 个)
ct-scans 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 103 个仓库COVID-19 Detection Chest X-rays and CT scans: COVID-19 Detection based on Chest X-rays and CT Scans using four Transfer Learning algorithms: VGG16, ResNet50, InceptionV3, Xception. The models were trained for 500 epochs on around 1000 Chest X-rays and around 750 CT Scan images on Google Colab GPU. A Flask App was later developed wherein user can…
AiAi.care project is teaching computers to "see" chest X-rays and interpret them how a human Radiologist would. We are using 700,000 Chest X-Rays + Deep Learning to build an FDA 💊 approved, open-source screening tool for Tuberculosis and Lung Cancer. After an MRMC clinical trial, AiAi CAD will be distributed for free to emerging nations, charita…
An official implementation of PCRLv2 (pre-training and fine-tuning code are included).
End-to-end Python CT volume preprocessing pipeline to convert raw DICOMs into clean 3D numpy arrays for ML. From paper Draelos et al. "Machine-Learning-Based Multiple Abnormality Prediction with Large-Scale Chest Computed Tomography Volumes."
Image-based COVID-19 diagnosis. Links to software, data, and other resources.
Fully automated code for Covid-19 detection from CT scans from paper: https://doi.org/10.1016/j.bspc.2021.102588
🔀 Medical software for Processing multi-Parametric images Pipelines
Machine learning models for multi-organ, multi-disease prediction in chest CT volumes. From paper Draelos et al. "Machine-Learning-Based Multiple Abnormality Prediction with Large-Scale Chest Computed Tomography Volumes."
Deep CNN for performing 3D super resolution on CT/MRI scans
Segmentation and Classification models for COVID CT scans (COVID, pneumonia, normal) based on Mask R-CNN.
A simple privacy-focused web panel in flask for labeling CT Scan's slices
A COVID-19 CT Scan Dataset Applicable in Machine Learning and Deep Learning
CNN's for bone segmentation of CT-scans.
CTSegNet is an end-to-end 3D segmentation package for large X-ray tomographic datasets using 2D fully convolutional neural networks (fCNN).
This is the official repository for Fast-nnUNet, a new fast model inference framework based on the nnUNet framework implementation.
Idiopathic pulmonary fibrosis (IPF) is a restrictive interstitial lung disease that causes lung function decline by lung tissue scarring. Although lung function decline is assessed by the forced vital capacity (FVC), determining the accurate progression of IPF remains a challenge. To address this challenge, we proposed Fibro-CoSANet, a novel end…
A repository containing deep learning models and evaluation methods for enhancing medical image segmentation in Computed Tomography (CT) scans, with a focus on U-Net variants, nnUNet, and Swin-UNet architectures.
Unity3d Prototype to manipulate Hounsfield units and create a 3D render of dicom images
该项目在 GitHub 上没有填写描述
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/ct-scans。
- 该话题在 GitHub 上共有 103 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
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- 当前 20 个项目累计 1481 Star,覆盖 6 种主要语言,数据更新于 2026-11-07。
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