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Found 4 papers, 1 papers with code
Influence of Prompting Strategies on Segment Anything Model (SAM) for Short-axis Cardiac MRI segmentation
We conduct a comprehensive investigation of the impact of different prompting strategies (including bounding boxes, positive points, negative points, and their combinations) on segmentation performance.
Attribute Regularized Soft Introspective Variational Autoencoder for Interpretable Cardiac Disease Classification
Interpretability is essential in medical imaging to ensure that clinicians can comprehend and trust artificial intelligence models.
Sparse annotation strategies for segmentation of short axis cardiac MRI
Further, annotating slices from the middle of volumes yields the most beneficial results in terms of segmentation performance, and the apical region the worst.
Attribute Regularized Soft Introspective VAE: Towards Cardiac Attribute Regularization Through MRI Domains
In this work, we propose the Attributed Soft Introspective VAE (Attri-SIVAE) by incorporating an attribute regularized loss, into the Soft-Intro VAE framework.
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