Oct 12, 2022 · The challenge aims to establish a public benchmark dataset to assess the effects of respiratory motion on image quality and examine the robustness of ...
The aim of this challenge is to assess the effects of respiratory motion on CMR imaging quality and examine the robustness of segmentation models.
The design of extreme cardiac MRI analysis challenge under respiratory motion (CMRxMotion Challenge) is described, which aims to establish a public ...
Oct 12, 2022 · This manuscript describes the design of extreme cardiac MRI analysis challenge under respiratory motion (CMRxMotion Challenge). The chal- lenge ...
Sep 11, 2024 · The challenge aims to establish a public benchmark dataset to assess the effects of respiratory motion on image quality and examine the ...
In this challenge, we introduce the CMRxMotion dataset, a realistic cardiac MRI dataset including extreme cases with different levels of respiratory motions. We ...
Jan 28, 2023 · In this paper, we have presented two different deep learning frameworks for CMR imaging quality assessment and automatic segmentation.
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The objective of establishing the CMRxUniversalRecon challenge (Toward Universal Reconstruction) is to provide a benchmark that enables the broader research ...
May 10, 2023 · Participants are expected to train models in their local computational environments and to submit docker containers on Synapse platform.
Cardiac magnetic resonance imaging (MRI) may suffer from motion-related artifacts resulting in non-diagnostic quality images.