医学图像诊断深度模型

五 3D

2016

1.《 V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation》

2.《3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation》

2017

1. 《H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes (IEEE Transactions on Medical Imaging)》

2018

1.《UNet&＃43;&＃43;: A Nested U-Net Architecture for Medical Image Segmentation (MICCAI)》
2.《nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation》
3.《LADDERNET: Multi-Path Networks Based on U-Net for Medical Image Segmentation》
4.《A Probabilistic U-Net for Segmentation of Ambiguous Images (NIPS)》
5.《3D RoI-aware U-Net for Accurate and Efficient Colorectal Cancer Segmentation》

2019

1.《MultiResUNet : Rethinking the U-Net Architecture for Multimodal Biomedical Image Segmentation》

2.《CE-Net: Context Encoder Network for 2D Medical Image Segmentation》

3.《A Partially Reversible U-Net for Memory-Efficient Volumetric Image Segmentation (MICCAI 2019)》

4.《3D U2-Net: A 3D Universal U-Net for Multi-Domain Medical Image Segmentation (MICCAI 2019)》

5.《3D Dilated Multi-Fiber Network for Real-time Brain Tumor Segmentation in MRI》

2020

2021

2022

六 各类数据集介绍&＃xff1a;

• 医学细胞分割数据集&＃xff1a;

在下面网址注册&＃xff0c;获得
http://brainiac2.mit.edu/isbi_challenge/

• 3D-医学细胞分割数据集&＃xff1a;

training set: https://osf.io/x9yns/
validation set: https://osf.io/xp5uf/
test set: https://osf.io/8jz7e/

• Google云&＃xff1a;Liver(肝脏)数据集

https://github.com/xmengli999/H-DenseUNet

• 3Dircadb:

3D-IRCADb (3D Image Reconstruction for Comparison of Algorithm Database) is a database includes several sets of anonymized medical images of patients and the manual segmentation of the various structures of interest performed by clinical experts.