Domain generalization for medical image analysis: A survey
Medical Image Analysis (MedIA) has become an essential tool in medicine and healthcare,
aiding in disease diagnosis, prognosis, and treatment planning, and recent successes in …
aiding in disease diagnosis, prognosis, and treatment planning, and recent successes in …
Domain Generalization for Medical Image Analysis: A Review
Medical image analysis (MedIA) has become an essential tool in medicine and healthcare,
aiding in disease diagnosis, prognosis, and treatment planning, and recent successes in …
aiding in disease diagnosis, prognosis, and treatment planning, and recent successes in …
Learning spectral-decomposited tokens for domain generalized semantic segmentation
The rapid development of Vision Foundation Model (VFM) brings inherent out-domain
generalization for a variety of down-stream tasks. Among them, domain generalized …
generalization for a variety of down-stream tasks. Among them, domain generalized …
A blockchain-empowered secure federated domain generalization framework for machinery fault diagnosis
The digitization transformation of traditional machinery and advances in artificial intelligence
have led to the development of data-driven machinery fault diagnosis methods. However …
have led to the development of data-driven machinery fault diagnosis methods. However …
Mind Marginal Non-Crack Regions: Clustering-Inspired Representation Learning for Crack Segmentation
Crack segmentation datasets make great efforts to obtain the ground truth crack or non-crack
labels as clearly as possible. However it can be observed that ambiguities are still inevitable …
labels as clearly as possible. However it can be observed that ambiguities are still inevitable …
Domain generalization in computational pathology: survey and guidelines
Deep learning models have exhibited exceptional effectiveness in Computational Pathology
(CPath) by tackling intricate tasks across an array of histology image analysis applications …
(CPath) by tackling intricate tasks across an array of histology image analysis applications …
Curriculum-based augmented fourier domain adaptation for robust medical image segmentation
Accurate and robust medical image segmentation is fundamental and crucial for enhancing
the autonomy of computer-aided diagnosis and intervention systems. Medical data …
the autonomy of computer-aided diagnosis and intervention systems. Medical data …
HarmoDT: Harmony Multi-Task Decision Transformer for Offline Reinforcement Learning
The purpose of offline multi-task reinforcement learning (MTRL) is to develop a unified policy
applicable to diverse tasks without the need for online environmental interaction. Recent …
applicable to diverse tasks without the need for online environmental interaction. Recent …
DCAM-NET: A novel domain generalization optic cup and optic disc segmentation pipeline with multi-region and multi-scale convolution attention mechanism
K Hua, X Fang, Z Tang, Y Cheng, Z Yu - Computers in Biology and …, 2023 - Elsevier
Fundus images are an essential basis for diagnosing ocular diseases, and using
convolutional neural networks has shown promising results in achieving accurate fundus …
convolutional neural networks has shown promising results in achieving accurate fundus …
A Novel Cross-Perturbation for Single Domain Generalization
Single domain generalization aims to enhance the ability of the model to generalize to
unknown domains when trained on a single source domain. However, the limited diversity in …
unknown domains when trained on a single source domain. However, the limited diversity in …