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nliang1995
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FLAIR: A Foundation LAnguage-Image model of the Retina for fundus image understanding.
C3F-CGAN: A Novel Coarse-Fine Feature Fusion based Conditional GAN for Generating Fundus Fluorescein Angiography from Ultra-Wide-angle Fundus Scanning Laser Ophthalmoscope
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Updated Jun 17, 2024
[ICPR'20] [Tensorflow] Synthesizing Fluorescein Angiography from Retinal Fundus Images using Attention based GAN
Retinal Vessel Segmentation on Fluorescein Angiography Retinal Images using U-NET
[TPAMI 2023] Multimodal Image Synthesis and Editing: The Generative AI Era
a retinal fundus dataset for eye disease diagnosis and fundus synthesis
[ICCV2021] [Tensorflow] Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers
[WACV 2019 Oral] Deep Micro-Dictionary Learning and Coding Network
The official repository of the paper "DeepM2CDL: Deep Multi-scale Multi-modal Convolutional Dictionary Learning Network" from IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
Buildings segmentation and multiple sclerosis lesions segmentation (Dictionary learning, Encoding, Classification)
Cross-Modal Dictionary Learning for RGB-D Segmentation with Missing Modalities.
binary/multi-class classification/regression for diabetic retinopathy detection(idrid eyepacs)
code and models for "Laplacian Pyramid Reconstruction and Refinement for Semantic Segmentation"
OphNet: A Large-Scale Video Benchmark for Ophthalmic Surgical Workflow Understanding
PyTorch implementation for Semantic Invariant Multi-view Clustering with Fully Incomplete Information (SMILE), TPAMI 2023.
[ICCV 2023] Harvard Glaucoma Detection and Progression: A Multimodal Multitask Dataset and Generalization-Reinforced Semi-Supervised Learning
Convolutional sparse coding (CSC) and convolutional dictionary learning (CDL) for off-the-grid events
Official implementation of Deep Convolutional Dictionary Learning for Image Denoising.
Code for "From Instance to Metric Calibration: A Unified Framework for Open-World Few-Shot Learning" in TPAMI 2023.
Medical Image Segmentation with Deep Reinforcement Learning
医学影像数据集列表 『An Index for Medical Imaging Datasets』
Training FCNNs from patches to full-sized images. A framework to train arbitrarily designed networks for medical image segmentation.