Applications of AI in multi-modal imaging for cardiovascular disease
Data for healthcare is diverse and includes many different modalities. Traditional
approaches to Artificial Intelligence for cardiovascular disease were typically limited to …
approaches to Artificial Intelligence for cardiovascular disease were typically limited to …
Medical image segmentation with domain adaptation: a survey
Deep learning (DL) has shown remarkable success in various medical imaging data
analysis applications. However, it remains challenging for DL models to achieve good …
analysis applications. However, it remains challenging for DL models to achieve good …
MyoPS-Net: Myocardial pathology segmentation with flexible combination of multi-sequence CMR images
Myocardial pathology segmentation (MyoPS) can be a prerequisite for the accurate
diagnosis and treatment planning of myocardial infarction. However, achieving this …
diagnosis and treatment planning of myocardial infarction. However, achieving this …
MyoPS: A benchmark of myocardial pathology segmentation combining three-sequence cardiac magnetic resonance images
Assessment of myocardial viability is essential in diagnosis and treatment management of
patients suffering from myocardial infarction, and classification of pathology on the …
patients suffering from myocardial infarction, and classification of pathology on the …
Towards enabling cardiac digital twins of myocardial infarction using deep computational models for inverse inference
Cardiac digital twins (CDTs) have the potential to offer individualized evaluation of cardiac
function in a non-invasive manner, making them a promising approach for personalized …
function in a non-invasive manner, making them a promising approach for personalized …
Aligning multi-sequence CMR towards fully automated myocardial pathology segmentation
Myocardial pathology segmentation (MyoPS) is critical for the risk stratification and treatment
planning of myocardial infarction (MI). Multi-sequence cardiac magnetic resonance (MS …
planning of myocardial infarction (MI). Multi-sequence cardiac magnetic resonance (MS …
DrFuse: Learning Disentangled Representation for Clinical Multi-Modal Fusion with Missing Modality and Modal Inconsistency
The combination of electronic health records (EHR) and medical images is crucial for
clinicians in making diagnoses and forecasting prognoses. Strategically fusing these two …
clinicians in making diagnoses and forecasting prognoses. Strategically fusing these two …
[HTML][HTML] MV-MS-FETE: Multi-view multi-scale feature extractor and transformer encoder for stenosis recognition in echocardiograms
Background: aortic stenosis is a common heart valve disease that mainly affects older
people in developed countries. Its early detection is crucial to prevent the irreversible …
people in developed countries. Its early detection is crucial to prevent the irreversible …
Artificial Intelligence in Image-based Cardiovascular Disease Analysis: A Comprehensive Survey and Future Outlook
Recent advancements in Artificial Intelligence (AI) have significantly influenced the field of
Cardiovascular Disease (CVD) analysis, particularly in image-based diagnostics. Our paper …
Cardiovascular Disease (CVD) analysis, particularly in image-based diagnostics. Our paper …
Towards Accurate Cardiac MRI Segmentation with Variational Autoencoder-Based Unsupervised Domain Adaptation
Accurate myocardial segmentation is crucial in the diagnosis and treatment of myocardial
infarction (MI), especially in Late Gadolinium Enhancement (LGE) cardiac magnetic …
infarction (MI), especially in Late Gadolinium Enhancement (LGE) cardiac magnetic …