6 papers
Bi-PT: Bidirectional Cross-Attention Point Transformers for Four-Chamber Heart Reconstruction from Sparse Cardiac MRI Data
Chenchuhui Hu, Shaoming Pan, Leon Axel +1
We propose Bi-PT, a pipeline for reconstructing 3D four-chamber human heart meshes from clinical sparsely sampled cardiac magnetic resonance imaging (CMR) data. This work addresses…
K-Prism: A Knowledge-Guided and Prompt Integrated Universal Medical Image Segmentation Model
Bangwei Guo, Yunhe Gao, Meng Ye +4
Medical image segmentation is fundamental to clinical decision-making, yet existing models remain fragmented. They are usually trained on single knowledge sources and specific to i…
Rate-My-LoRA: Efficient and Adaptive Federated Model Tuning for Cardiac MRI Segmentation
Xiaoxiao He, Haizhou Shi, Ligong Han +7
Cardiovascular disease (CVD) and cardiac dyssynchrony are major public health problems in the United States. Precise cardiac image segmentation is crucial for extracting quantitati…
VerSe: Integrating Multiple Queries as Prompts for Versatile Cardiac MRI Segmentation
Bangwei Guo, Meng Ye, Yunhe Gao +3
Despite the advances in learning-based image segmentation approach, the accurate segmentation of cardiac structures from magnetic resonance imaging (MRI) remains a critical challen…
Learning Volumetric Neural Deformable Models to Recover 3D Regional Heart Wall Motion from Multi-Planar Tagged MRI
Meng Ye, Bingyu Xin, Bangwei Guo +2
Multi-planar tagged MRI is the gold standard for regional heart wall motion evaluation. However, accurate recovery of the 3D true heart wall motion from a set of 2D apparent motion…
Neural Deformable Models for 3D Bi-Ventricular Heart Shape Reconstruction and Modeling from 2D Sparse Cardiac Magnetic Resonance Imaging
Meng Ye, Dong Yang, Mikael Kanski +2
We propose a novel neural deformable model (NDM) targeting at the reconstruction and modeling of 3D bi-ventricular shape of the heart from 2D sparse cardiac magnetic resonance (CMR…