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Found 7 papers, 6 papers with code
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 deep learning (DL) have made significant contributions to its advances.
SADM: Sequence-Aware Diffusion Model for Longitudinal Medical Image Generation
To this end, we propose a sequence-aware diffusion model (SADM) for the generation of longitudinal medical images.
XADLiME: eXplainable Alzheimer's Disease Likelihood Map Estimation via Clinically-guided Prototype Learning
By considering this pseudo map as an enriched reference, we employ an estimating network to estimate the AD likelihood map over a 3D sMRI scan.
Learn-Explain-Reinforce: Counterfactual Reasoning and Its Guidance to Reinforce an Alzheimer's Disease Diagnosis Model
Existing studies on disease diagnostic models focus either on diagnostic model learning for performance improvement or on the visual explanation of a trained diagnostic model.
Born Identity Network: Multi-way Counterfactual Map Generation to Explain a Classifier's Decision
Specifically, our proposed BIN consists of two core components: Counterfactual Map Generator and Target Attribution Network.
Mutual Information-driven Subject-invariant and Class-relevant Deep Representation Learning in BCI
In this paper, we propose a novel framework that learns class-relevant and subject-invariant feature representations in an information-theoretic manner, without using adversarial learning.
A Plug-in Method for Representation Factorization in Connectionist Models
In this article, we focus on decomposing latent representations in generative adversarial networks or learned feature representations in deep autoencoders into semantically controllable factors in a semisupervised manner, without modifying the original trained models.
