brats2018 开源项目推荐（16 个）

black0017 /MedicalZooPytorch

基于pytorch的深度学习框架，用于多模式2D/3D医学图像分割

IAmSuyogJadhav /3d-mri-brain-tumor-segmentation-using-autoencoder-regularization

Keras implementation of the paper "3D MRI brain tumor segmentation using autoencoder regularization" by Myronenko A. (https://arxiv.org/abs/1810.11654).

athon2 /BraTS2018_NvNet

NvNet的实现

lachinov /brats2019

该项目在 GitHub 上没有填写描述

adhaka3 /Pyadiomics-based-glioma-grading

This is a complete guide on how to do Pyradiomics based feature extraction and then, build a model to calculate the grade of glioma.

AHMEDSANA /Binary-Class-Brain-Tumor-Segmentation-Using-UNET

We segmented the Brain tumor using Brats dataset and as we know it is in 3D format we used the slicing method in which we slice the images in 2D form according to its 3 axis and then giving the model for training then combining waits to segment brain tumor. We used UNET model for our segmentation.

edukait /glioma-classification

The purpose of this project is to be able to automatically and efficiently segment and classify high-grade and low-grade gliomas.

Bidur-Khanal /MVAAL-medical-images

In this work we present a task-agnostic Multimodal Variational Aversarial Active Learning (M-VAAL) for sampling the most informative samples for annotation in various Medical Image Analysis Downstream tasks, such as segmentation, and classification.

lachinov /brats2018-graphlabunn

该项目在 GitHub 上没有填写描述

pykao /BraTS2018-survival-prediction

We provide a method to extract the tractographic features from structural MR images for patients with brain tumor

AHMEDSANA /Four-class-Brain-tumor-segmentation

We segmented the Brain tumor using Brats dataset and as we know it is in 3D format we used the slicing method in which we slice the images in 2D form according to its 3 axis and then giving the model for training then combining waits to segment brain tumor. We used UNET model for training our dataset.

viniavskyi-ostap /brain_tumor_segmentation

Implementation of different techniques for segmentation of tumors in MRI images.

pheonix-18 /3D-Unet-BraTS-PyTorch

Tumor Doc: Brain tumor segmention using Deep Learning Method 1

MartinMa28 /brain-tumor-segmentation

Semantic segmentation for brain tumors

numaanfarooq /Brain_Tumour_Segmentation_and_Survival_Prediction_Using_Deep_Learning

This project aims to create a deep learning based model for the segmentation of brain tumours and their subregions from MRI scans, as well as the prediction of patient survival . The segmentation is performed using a U-Net architecture, while survival prediction is done using CNN models.

HarmonyHI /MedSig

脑肿瘤 MRI 分割与病例管理系统：Vue 3 + Element Plus 前端，Django 4.2 + PyTorch（DMFNet）后端，数据集 BraTS 2018