cardiac magnetic resonance imaging
PulseAugur coverage of cardiac magnetic resonance imaging — every cluster mentioning cardiac magnetic resonance imaging across labs, papers, and developer communities, ranked by signal.
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New TetHeart framework reconstructs 4D heart mesh from sparse cardiac MRI
Researchers have developed TetHeart, a novel end-to-end framework for reconstructing 4D heart mesh from cardiac MRI sequences. This system can process both complete MRI stacks and sparse, real-time slice observations, m…
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AI applications in cardiac amyloidosis diagnosis reviewed
A new review paper details the application of artificial intelligence across the diagnostic pathway for cardiac amyloidosis. The paper categorizes AI models by clinical tasks such as screening, detection, quantification…
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Bi-PT pipeline reconstructs 3D heart meshes from sparse cardiac MRI data
Researchers have developed Bi-PT, a novel pipeline for reconstructing 3D four-chamber heart meshes from sparse cardiac MRI data. This method utilizes bidirectional cross-attention point transformers to learn robust poin…
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Metadata-driven pre-training boosts cardiac MRI models
Researchers have developed MetaCLIP-CMR, a novel framework for pre-training cardiac MRI foundation models by leveraging structured acquisition metadata. This approach converts imaging modality, anatomical view, scanner …
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New latent ODE model enhances heart failure prediction from cardiac MRI
Researchers have developed a novel latent dynamical model using neural ordinary differential equations (ODEs) to analyze cardiac magnetic resonance imaging (CMR) data. This model encodes bi-ventricular anatomy and full-…
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CardioMorphNet predicts cardiac motion using shape-guided Bayesian deep learning
Researchers have developed CardioMorphNet, a novel Bayesian recurrent deep learning framework for predicting cardiac motion from short-axis cardiac MRI images. This method utilizes a recurrent variational autoencoder an…
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CardioLens evaluation reveals MLLMs struggle with clinical cardiac MRI tasks
Researchers have developed CardioLens, a new evaluation testbed for multimodal large language models (MLLMs) using multi-sequence cardiac MRI data. The testbed, constructed from private hospital archives, contains over …
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New set-based registration framework generalizes across cardiac MRI protocols
Researchers have developed a new set-based groupwise registration framework called \AnyTwoReg for cardiac MRI sequences. This method treats input data as an unordered set, decoupling network design from sequence length …