activity
20172021
most citedLearning MRI Artifact Removal With Unpaired Data

50 citations · 111 across the 12 of their papers we have counts for

collaborators

22 papers

eess.IV2021

Dual Shape Guided Segmentation Network for Organs-at-Risk in Head and Neck CT Images

Shuai Wang, Theodore Yanagihara, Bhishamjit Chera +3

The accurate segmentation of organs-at-risk (OARs) in head and neck CT images is a critical step for radiation therapy of head and neck cancer patients. However, manual delineation…

eess.IV202150 cited

Learning MRI Artifact Removal With Unpaired Data

Siyuan Liu, Kim-Han Thung, Liangqiong Qu +3

Retrospective artifact correction (RAC) improves image quality post acquisition and enhances image usability. Recent machine learning driven techniques for RAC are predominantly ba…

eess.IV20215 cited

Learning Multi-Site Harmonization of Magnetic Resonance Images Without Traveling Human Phantoms

Siyuan Liu, Pew-Thian Yap

Harmonization improves data consistency and is central to effective integration of diverse imaging data acquired across multiple sites. Recent deep learning techniques for harmoniz…

cs.CV2021

A Self-Supervised Deep Framework for Reference Bony Shape Estimation in Orthognathic Surgical Planning

Deqiang Xiao, Hannah Deng, Tianshu Kuang +11

Virtual orthognathic surgical planning involves simulating surgical corrections of jaw deformities on 3D facial bony shape models. Due to the lack of necessary guidance, the planni…

eess.IV20212 cited

Real-Time Mapping of Tissue Properties for Magnetic Resonance Fingerprinting

Yilin Liu, Yong Chen, Pew-Thian Yap

Magnetic resonance Fingerprinting (MRF) is a relatively new multi-parametric quantitative imaging method that involves a two-step process: (i) reconstructing a series of time frame…

q-bio.NC20211 cited

Altered connectedness of the brain chronnectome during the progression of Alzheimer's disease

M. Ghanbari, Z. Zhou, L-M. Hsu +5

Graph theory has been extensively used to investigate brain network topology and its changes in disease cohorts. However, many graph theoretic analysis-based brain network studies…