Abstract
Purpose: Accurate 3D MRI-ultrasound (US) deformable registration is critical for real-time guidance in high-dose-rate (HDR) prostate brachytherapy. We present a weakly supervised spatial implicit neural representation (SINR) method to address modality differences and pelvic anatomy challenges. Methods: The framework uses sparse surface supervision from MRI/US segmentations instead of dense intensity matching. SINR models deformations as continuous spatial functions, with patient-specific surface priors guiding a stationary velocity field for biologically plausible deformations. Validation included 20 public Prostate-MRI-US-Biopsy cases and 10 institutional HDR cases, evaluated via Dice similarity coefficient (DSC), mean surface distance (MSD), and 95% Hausdorff distance (HD95). Results: The proposed method achieved robust registration. For the public dataset, prostate DSC was $0.93 \pm 0.05$, MSD $0.87 \pm 0.10$ mm, and HD95 $1.58 \pm 0.37$ mm. For the institutional dataset, prostate CTV achieved DSC $0.88 \pm 0.09$, MSD $1.21 \pm 0.38$ mm, and HD95 $2.09 \pm 1.48$ mm. Bladder and rectum performance was lower due to ultrasound's limited field of view. Visual assessments confirmed accurate alignment with minimal discrepancies. Conclusion: This study introduces a novel weakly supervised SINR-based approach for 3D MRI-US deformable registration. By leveraging sparse surface supervision and spatial priors, it achieves accurate, robust, and computationally efficient registration, enhancing real-time image guidance in HDR prostate brachytherapy and improving treatment precision.
Abstract (translated)
目的：在高剂量率（HDR）前列腺组织间放射治疗中，精确的3D MRI-超声波（US）可变形配准对于实时引导至关重要。本文介绍了一种基于弱监督的空间隐式神经表示（SINR）方法来解决模态差异和骨盆解剖结构挑战。 方法：该框架使用来自MRI/US分割的稀疏表面监督，而不是密集强度匹配。SINR模型将变形视为连续空间函数，并通过特定于患者的表面先验指导一个静态速度场以实现生物合理的变形。验证包括20个公开的前列腺-MRI-US-活检案例和10个机构HDR案例，在Dice相似系数（DSC）、平均面距离（MSD）和95% Hausdorff距离（HD95）方面进行评估。 结果：所提出的方法实现了稳健的配准。对于公共数据集，前列腺DSC为$0.93 \pm 0.05$，MSD为$0.87 \pm 0.10$毫米，HD95为$1.58 \pm 0.37$毫米。对于机构数据集，前列腺CTV的DSC为$0.88 \pm 0.09$，MSD为$1.21 \pm 0.38$毫米，HD95为$2.09 \pm 1.48$毫米。由于超声波有限的视野范围，膀胱和直肠的表现较低。视觉评估确认了准确对齐且差异很小。 结论：本研究介绍了一种基于弱监督SINR的新方法用于3D MRI-US可变形配准。通过利用稀疏表面监督和空间先验信息，该方法实现了准确、稳健且计算效率高的配准，从而提高了HDR前列腺组织间放射治疗中的实时图像引导精度，并改善了治疗的精确度。
URL
https://arxiv.org/abs/2503.14395
