linli_mir (llmir)

llmir

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Company:PhD@HKU-SUSTech

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linli_mir's repositories

FedICRA

The official implementation of the paper "Unifying and Personalizing Weakly-supervised Federated Medical Image Segmentation via Adaptive Representation and Aggregation".

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.

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YoloCurvSeg

[MedIA'23] "YoloCurvSeg: You only label one noisy skeleton for vessel-style curvilinear structure segmentation".

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.

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VesselSeg-Pytorch

Retinal vessel segmentation toolkit based on pytorch

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awesome-federated-learning

A collection of AWESOME things about federated learning.

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CPFNet_Project

This is a pytorch project about medical segmentation

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da-sac

Self-supervised Augmentation Consistency for Adapting Semantic Segmentation (CVPR 2021)

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DANet

Dual Attention Network for Scene Segmentation (CVPR2019)

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DetectoRS

DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution

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FedDG-ELCFS

[CVPR'21] FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space

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focusnet-alpha

Code for Focusnet (ISBI2019) and FocusnetAlpha

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IterNet

IterNet: Retinal Image Segmentation Utilizing Structural Redundancy in Vessel Networks. High-accuracy medical retina (eye) image segmentation.

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Masking-Augmentation-Opencv-Keras-Image-Processing

Mask creation for segmentation task using opencv and Image augmentation tasks with imgaug library

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Patho-GAN

Patho-GAN: interpretation + medical data augmentation. Code for paper work "Explainable Diabetic Retinopathy Detection and Retinal Image Generation"

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PC-CHiP

Pan-Cancer Computational Histopathology

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prepare_detection_dataset

convert dataset to coco/voc format

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py-hausdorff

Fast computation of Hausdorff distance in Python

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recurrent-unet

ICCV 2019: Recurrent U-Net for Resource Constraint Segmentation

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SA-UNet

The open source code of SA-UNet: Spatial Attention U-Net for Retinal Vessel Segmentation.

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SeqNet

Joint Learning of Vessel Segmentation and Artery/Vein Classification

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toolbox

various tools such as label-tools , data-augmentation , etc.

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yolov5

YOLOv5 in PyTorch > ONNX > CoreML > iOS

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