Search Results for author:
Found 8 papers, 4 papers with code
SeATrans: Learning Segmentation-Assisted diagnosis model via Transformer
To model the segmentation-diagnosis interaction, SeA-block first embeds the diagnosis feature based on the segmentation information via the encoder, and then transfers the embedding back to the diagnosis feature space by a decoder.
Learning self-calibrated optic disc and cup segmentation from multi-rater annotations
In this paper, we propose a novel neural network framework to learn OD/OC segmentation from multi-rater annotations.
One Hyper-Initializer for All Network Architectures in Medical Image Analysis
Pre-training is essential to deep learning model performance, especially in medical image analysis tasks where limited training data are available.
Contrastive Centroid Supervision Alleviates Domain Shift in Medical Image Classification
Deep learning based medical imaging classification models usually suffer from the domain shift problem, where the classification performance drops when training data and real-world data differ in imaging equipment manufacturer, image acquisition protocol, patient populations, etc.
Opinions Vary? Diagnosis First!
Motivated by the observation that OD/OC segmentation is often used for the glaucoma diagnosis clinically, in this paper, we propose a novel strategy to fuse the multi-rater OD/OC segmentation labels via the glaucoma diagnosis performance.
Progressive Hard-case Mining across Pyramid Levels for Object Detection
Based on focal loss with ATSS-R50, our approach achieves 40. 5 AP, surpassing the state-of-the-art QFL (Quality Focal Loss, 39. 9 AP) and VFL (Varifocal Loss, 40. 1 AP).
Robust Collaborative Learning of Patch-level and Image-level Annotations for Diabetic Retinopathy Grading from Fundus Image
As a result, it exploits more discriminative features for DR grading.
Residual-CycleGAN based Camera Adaptation for Robust Diabetic Retinopathy Screening
How can we train a classification model on labeled fundus images ac-quired from only one camera brand, yet still achieves good performance on im-ages taken by other brands of cameras?
