Name: Xiangde Luo
Type: User
Company: West China Hospital
Bio: A researcher focused on AI for Healthcare and maintained several medical datasets (WORD, SegRap2023, LNCTVSeg, RAOS) and codebases (SSL4MIS, WSL4MIS).
Location: Chengdu
Blog: https://luoxd1996.github.io
Xiangde Luo's Projects
A repository with a basic layer of 3D deformable receptive field for 3D VoxCNN and 3D VoxResNet
Efficient Segmentation for Volumetric Data
3D VQ-VAE-2 for high-resolution CT scan synthesis
[RedJournal2023]Comprehensive evaluation of a deep learning model for automatic organs at risk segmentation on heterogeneous computed tomography images for abdominal radiotherapy.
ACFNet: Attentional Class Feature Network for Semantic Segmentation.(ICCV2019)
[IEEE JBHI] Reinventing 2D Convolutions for 3D Images - 1 line of code to convert pretrained 2D models to 3D!
Implementation of active contour loss function
Awesome Source-Free Active Domain Adaptation for Medical Image Analysis
Using AI to accelerate adaptive radiotherapy, automatic GTVs, CTVs, OARs delineation, dose estimation, and survival prediction.
Active Learning for Generalizable Nasopharyngeal Carcinoma Delineation Across Multiple Centers and Raters
Active Learning for Medical Image Segmentation
Awesome Incremental Learning
A curated list of resources for Learning with Noisy Labels
:scroll: An up-to-date & curated list of awesome semi-supervised learning papers, methods & resources.
code of Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations (CVPR2020 oral)
Implement of NvNet
Code for Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation.
A baseline for CheXpert Challenge 2019 [Top 3(09/30/2019)]
pyTorch implementation of clDice
The standard package for machine learning with noisy labels and finding mislabeled data in Python.
CPM-Net: A 3D Center-Points Matching Network for Pulmonary Nodule Detection in CT Scans
Python packaging for CPTAC data
A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography
Semi-supervised semantic segmentation needs strong, varied perturbations
CV岗常见面试题(欢迎大家补充!!!)
Related medical image dataset from OpenMedLab and others.
Deep Active Learning