Pinned Repositories
Andrew-Ng-Deep-Learning-notes
吴恩达《深度学习》系列课程笔记及代码
Andrew_Ng_DL_Assignment
微专业: 吴恩达 深度学习工程师 作业
DCDA
FedICRA
The official implementation of the paper "Unifying and Personalizing Weakly-supervised Federated Medical Image Segmentation via Adaptive Representation and Aggregation".
FedLPPA
Official repository for the paper "FedLPPA: Learning Personalized Prompt and Aggregation for Federated Weakly-supervised Medical Image Segmentation".
LovaszSoftmax
Code for the Lovász-Softmax loss (CVPR 2018)
MultitaskOCTA
This repository is an official PyTorch implementation of the paper "BSDA-Net: A Boundary Shape and Distance Aware Joint Learning Framework for Segmenting and Classifying OCTA Images", MICCAI 2021.
The-SUSTech-SYSU-dataset-for-automated-exudate-detection-and-diabetic-retinopathy-grading
Automated detection of exudates from fundus images plays an important role in diabetic retinopathy (DR) screening and evaluation, for which supervised or semi-supervised learning methods are typically preferred. However, a potential limitation of supervised and semi-supervised learning based detection algorithms is that they depend substantially on the sample size of training data and the quality of annotations, which is the fundamental motivation of this work. In this study, we construct a dataset containing 1219 fundus images (from DR patients and healthy controls) with annotations of exudate lesions. In addition to exudate annotations, we also provide four additional labels for each image: leftversus- right eye label, DR grade (severity scale) from three different grading protocols, the bounding box of the optic disc (OD), and fovea location. This dataset provides a great opportunity to analyze the accuracy and reliability of different exudate detection, OD detection, fovea localization, and DR classification algorithms. Moreover, it will facilitate the development of such algorithms in the realm of supervised and semi-supervised learning.
VesselSeg-Pytorch
Retinal vessel segmentation toolkit based on pytorch
YoloCurvSeg
[MedIA'23] "YoloCurvSeg: You only label one noisy skeleton for vessel-style curvilinear structure segmentation".
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