25 citations · 128 across the 49 of their papers we have counts for
19 papers · 1 filter
Interpretable and backpropagation-free Green Learning for efficient multi-task echocardiographic segmentation and classification
Jyun-Ping Kao, Jiaxin Yang, C. -C. Jay Kuo +1
Echocardiography is a cornerstone for managing heart failure (HF), with Left Ventricular Ejection Fraction (LVEF) being a critical metric for guiding therapy. However, manual LVEF…
Cross-Modal Fine-Tuning of 3D Convolutional Foundation Models for ADHD Classification with Low-Rank Adaptation
Jyun-Ping Kao, Shinyeong Rho, Shahar Lazarev +5
Early diagnosis of attention-deficit/hyperactivity disorder (ADHD) in children plays a crucial role in improving outcomes in education and mental health. Diagnosing ADHD using neur…
Brightness-Invariant Tracking Estimation in Tagged MRI
Zhangxing Bian, Shuwen Wei, Xiao Liang +10
Magnetic resonance (MR) tagging is an imaging technique for noninvasively tracking tissue motion in vivo by creating a visible pattern of magnetization saturation (tags) that defor…
Semi-Supervised Bone Marrow Lesion Detection from Knee MRI Segmentation Using Mask Inpainting Models
Shihua Qin, Ming Zhang, Juan Shan +3
Bone marrow lesions (BMLs) are critical indicators of knee osteoarthritis (OA). Since they often appear as small, irregular structures with indistinguishable edges in knee magnetic…
Principled Feature Disentanglement for High-Fidelity Unified Brain MRI Synthesis
Jihoon Cho, Jonghye Woo, Jinah Park
Multisequence Magnetic Resonance Imaging (MRI) provides a more reliable diagnosis in clinical applications through complementary information across sequences. However, in practice,…
Disentangled Multimodal Brain MR Image Translation via Transformer-based Modality Infuser
Jihoon Cho, Xiaofeng Liu, Fangxu Xing +4
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 mul…