Disentangled Multimodal Brain MR Image Translation via Transformer-based Modality Infuser

no code implementations • 1 Feb 2024 • Jihoon Cho, Xiaofeng Liu, Fangxu Xing, Jinsong Ouyang, Georges El Fakhri, Jinah Park, Jonghye Woo

Multimodal Magnetic Resonance (MR) Imaging plays a crucial role in disease diagnosis due to its ability to provide complementary information by analyzing a relationship between multimodal images on the same subject.

Brain Tumor Segmentation Translation +1

Posterior Estimation for Dynamic PET imaging using Conditional Variational Inference

no code implementations • 24 Oct 2023 • Xiaofeng Liu, Thibault Marin, Tiss Amal, Jonghye Woo, Georges El Fakhri, Jinsong Ouyang

Specifically, we counteract the information loss in the forward process by introducing latent variables.

Variational Inference

Posterior Estimation Using Deep Learning: A Simulation Study of Compartmental Modeling in Dynamic PET

no code implementations • 17 Mar 2023 • Xiaofeng Liu, Thibault Marin, Tiss Amal, Jonghye Woo, Georges El Fakhri, Jinsong Ouyang

Purpose: This work aims at using deep learning to efficiently estimate posterior distributions of imaging parameters, which in turn can be used to derive the most probable parameters as well as their uncertainties.

Bayesian Inference

Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference

no code implementations • 22 Jul 2021 • Xiaofeng Liu, Bo Hu, Linghao Jin, Xu Han, Fangxu Xing, Jinsong Ouyang, Jun Lu, Georges El Fakhri, Jonghye Woo

In this work, we propose a domain generalization (DG) approach to learn on several labeled source domains and transfer knowledge to a target domain that is inaccessible in training.

Bayesian Inference Domain Generalization