Accelerating image acquisition for cardiac magnetic resonance imaging (CMRI) is a critical task. CMRxRecon2024 challenge aims to set the state of the art for multi-contrast CMR reconstruction. This paper presents HyperCMR, a novel framework designed to accelerate the reconstruction of multi-contrast cardiac magnetic resonance (CMR) images. HyperCMR enhances the existing PromptMR model by incorporating advanced loss functions, notably the innovative Eagle Loss, which is specifically designed to recover missing high-frequency information in undersampled k-space. Extensive experiments conducted on the CMRxRecon2024 challenge dataset demonstrate that HyperCMR consistently outperforms the baseline across multiple evaluation metrics, achieving superior SSIM and PSNR scores.

翻译：加速心脏磁共振成像（CMRI）的图像采集是一项关键任务。CMRxRecon2024挑战赛旨在为多对比度CMR重建设定最新技术标准。本文提出了HyperCMR，一个旨在加速多对比度心脏磁共振（CMR）图像重建的新型框架。HyperCMR通过引入先进的损失函数（特别是创新的Eagle Loss）来增强现有的PromptMR模型，该损失函数专为恢复欠采样k空间中缺失的高频信息而设计。在CMRxRecon2024挑战赛数据集上进行的大量实验表明，HyperCMR在多项评估指标上始终优于基线模型，获得了更优的SSIM和PSNR分数。