点分布模型中超声图像切片定位研究
On the Localization of Ultrasound Image Slices within Point Distribution Models
AI总结：
针对甲状腺超声诊断中切片定位困难，提出基于对比度量学习的多模态配准框架，将超声切片配准到三维形状模型，实现平均误差1.2毫米（患者特异性）和4.6毫米（SSM）的定位精度。
摘要：
甲状腺疾病最常使用高分辨率超声（US）进行诊断。纵向结节追踪是监测病理性甲状腺形态变化的关键诊断方案。然而，由于在脑海中维持器官三维重建的固有挑战，该任务给临床医生带来了巨大的认知负担。因此，我们提出一个框架，用于在三维形状表示中自动定位超声图像切片，以减轻此类超声诊断的执行难度。我们的方法通过对比度量学习，学习超声图像块与个体甲状腺形状的三维表面（或统计形状模型（SSM）形式的统计聚合）之间的共同潜在嵌入空间。利用跨模态配准和Procrustes分析，我们利用模型的特征将超声切片配准到甲状腺形状的三维网格表示上。我们证明，我们的多模态配准框架可以在患者特异性器官的三维表面拓扑和SSM的平均形状上定位图像。实验结果表明，在患者特异性三维解剖结构上，切片位置预测平均误差为1.2毫米，在SSM上为4.6毫米，这体现了其在超声采集过程中切片定位的实用性。代码公开可用：https://github.com/vuenc/slice-to-shape
英文摘要：
Thyroid disorders are most commonly diagnosed using high-resolution Ultrasound (US). Longitudinal nodule tracking is a pivotal diagnostic protocol for monitoring changes in pathological thyroid morphology. This task, however, imposes a substantial cognitive load on clinicians due to the inherent challenge of maintaining a mental 3D reconstruction of the organ. We thus present a framework for automated US image slice localization within a 3D shape representation to ease how such sonographic diagnoses are carried out. Our proposed method learns a common latent embedding space between US image patches and the 3D surface of an individual's thyroid shape, or a statistical aggregation in the form of a statistical shape model (SSM), via contrastive metric learning. Using cross-modality registration and Procrustes analysis, we leverage features from our model to register US slices to a 3D mesh representation of the thyroid shape. We demonstrate that our multi-modal registration framework can localize images on the 3D surface topology of a patient-specific organ and the mean shape of an SSM. Experimental results indicate slice positions can be predicted within an average of 1.2 mm of the ground-truth slice location on the patient-specific 3D anatomy and 4.6 mm on the SSM, exemplifying its usefulness for slice localization during sonographic acquisitions. Code is publically available: \href{https://github.com/vuenc/slice-to-shape}{https://github.com/vuenc/slice-to-shape}
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