Left Ventricle Segmentation

Benchmarks archive 2025-07-28

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Libraries

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Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

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Most implemented papers archive 2025-07-28

5 shown of 5 papers with code (25 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• HDL: Hybrid Deep Learning for the Synthesis of Myocardial Velocity Maps in Digital Twins for Cardiac Analysis
  9 Mar 2022 2 repositories listed
  A core part of digital healthcare twins is model-based data synthesis, which permits the generation of realistic medical signals without requiring to cope with the modelling complexity of anatomical and biochemical…
• EchoNet-Quality: Denoising Echocardiograms via Deep Generative Modeling of Ultrasound Noise
  29 Apr 2025 1 repository listed
  Echocardiography (echo), or cardiac ultrasound, is the most widely used imaging modality for cardiac form and function due to its relatively low cost, rapid acquisition time, and non-invasive nature.
• Contrastive Pretraining for Echocardiography Segmentation with Limited Data
  16 Jan 2022 1 repository listed
  Our results show that contrastive pretraining helps improve the performance on left ventricle segmentation, particularly when annotated data is scarce.
• Curriculum semi-supervised segmentation
  10 Apr 2019 1 repository listed
  This study investigates a curriculum-style strategy for semi-supervised CNN segmentation, which devises a regression network to learn image-level information such as the size of a target region.
• End-to-end Learning of Convolutional Neural Net and Dynamic Programming for Left Ventricle Segmentation
  2 Dec 2018 1 repository listed
  Differentiable programming is able to combine different functions or programs in a processing pipeline with the goal of applying end-to-end learning or optimization.