SENSE加速脑部MRI中的解剖学保真伪影抑制
Anatomically Faithful Artifact Suppression in SENSE Accelerated Brain MRI
浏览论文内容
中文总结 AI 辅助
本文提出解剖感知残差注意力网络（ART-Net），通过广义自注意力和残差伪影正则化抑制SENSE4加速脑MRI的混叠伪影，在保留解剖信息的同时提升图像质量，支持可靠的下游定量分析。
中文摘要 AI 辅助
背景：四倍加速灵敏度编码（SENSE4）可缩短脑部MRI采集时间，但可能放大噪声并在常规重建后产生残余混叠伪影。目的：评估图像域细化框架能否在保留用于定量测量的解剖信息的同时，提高SENSE4脑部MRI的质量。方法：在这项前瞻性配对研究中，80名参与者接受了全采样和四倍加速SENSE T1加权MRI。我们开发了一种解剖感知残差注意力网络（ART-Net），通过广义自注意力和基于相关性的残差伪影正则化来细化加速重建。参与者级划分产生了训练、验证和独立测试队列（45/5/30名参与者）。独立测试队列接受了定量、基于分割和盲法放射科医生对图像质量和解剖保留的评估。结果：ART-Net表现出极具竞争力的重建性能，在评估方法中实现了最高的峰值信噪比（31.03±2.88 dB）和结构相似性指数（0.963±0.022）。它还表现出改进的解剖保真度，在与萎缩评估相关的内侧颞叶结构（0.8824±0.0827）和全脑区域（0.8857±0.0885）中获得了数值最高的Dice系数。此外，ART-Net改善了梯度保真度、区域对比度保留和放射科医生评分的结构质量。结论：在单中心、保留测试队列中，ART-Net改善了SENSE4与全采样T1加权图像之间的一致性，同时保持了分割衍生的解剖测量。这些发现表明，ART-Net可能通过提高图像保真度和实现可靠的下游解剖分析来支持加速脑部MRI。
英文摘要
Background: Four-fold accelerated sensitivity encoding (SENSE4) can shorten brain MRI acquisition time but may amplify noise and result in residual aliasing artifacts after conventional reconstruction. Purpose: To evaluate whether an image-domain refinement framework can improve the quality of SENSE4 brain MRI while preserving anatomical information for quantitative measurements. Methods: In this prospective paired study, 80 participants underwent fully sampled and four-fold accelerated SENSE T1-weighted MRI. We developed an Anatomy-aware Residual Attention Network (ART-Net) to refine accelerated reconstructions through generalized self-attention and correlation-based residual artifact regularization. Participant-level splitting yielded training, validation, and independent test cohort (45/5/30 participants). The independent test cohort underwent quantitative, segmentation-based, and blinded radiologist assessments of image quality and anatomical preservation. Results: ART-Net demonstrated highly competitive reconstruction performance, achieving the highest peak signal-to-noise ratio (31.03 +/- 2.88 dB) and structural similarity index (0.963 +/- 0.022) among evaluated methods. It also demonstrated improved anatomical fidelity, with numerically highest Dice coefficients for medial temporal structures relevant to atrophy assessment (0.8824 +/- 0.0827) and whole-brain regions (0.8857 +/- 0.0885). Moreover, ART-Net improved gradient fidelity, regional contrast preservation, and radiologist-rated structural quality. Conclusion: ART-Net improved agreement between SENSE4 and fully sampled T1-weighted images in a single-center, held-out test cohort while maintaining segmentation-derived anatomical measurements. These findings suggest that ART-Net may support accelerated brain MRI by improving image fidelity and enabling reliable downstream anatomical analysis.
发表机构
- East China Normal University（华东师范大学）
- Affiliated Hospital of Guizhou Medical University（贵州医科大学附属医院）
- West China Hospital, Sichuan University（四川大学华西医院）
- Chinese Academy of Medical Sciences（中国医学科学院）
- RadioDynamic Medical（镭动医疗）
- Lucile Packard Children’s Hospital（露西尔·帕卡德儿童医院）
机构由 AI 辅助整理，请以论文原文为准。
