Titlebook: Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPig; 10th International W Mihaela Pop,Maxi

Contort

aggravate

Multimodal Cardiac Segmentation Using Disentangled Representation Learninguence’s images (modality hereafter) is treated in isolation. We propose a method suitable for multimodal and multi-input learning and analysis, that disentangles anatomical and imaging factors, and . anatomical content across the modalities to extract more accurate segmentation masks. Mis-registrati

arbiter

Formidable

破译

负担

Coeval

4D CNN for Semantic Segmentation of Cardiac Volumetric Sequencestwork to predict temporally consistent segmentations and compare with traditional 3D segmentation approaches. We demonstrate the feasibility of the 4D CNN and establish its performance on cardiac 4D CCTA (video: ..).

赦免

Multimodal Cardiac Segmentation Using Disentangled Representation Learningdemonstrate applications in Late Gadolinium Enhanced (LGE) and cine MRI segmentation. We show that multi-input outperforms single-input models, and that we can train a (semi-supervised) model with few (or no) annotations for one of the modalities. Code is available at ..

Patrimony

End-to-end Cardiac Ultrasound Simulation for a Better Understanding of Image Qualityh a pipeline enables to vary every parameter in order to quantitatively evaluate its impact on the final image quality. We present here first results on classical ultrasound phantoms and a digital heart. The utility of this pipeline is exemplified with the impact of ribs on the resulting cardiac ultrasound image.

Ige326

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/s/image/876376.jpg