基于拓扑保持Transformer的CBCT-CT配准：归一化梯度场引导用于鼻咽癌
Topology-preserved transformer-based CBCT-CT registration via normalized gradient field guidance for nasopharyngeal carcinoma.
文献信息
| PMID | 42740817 |
|---|---|
| 原文 | 在 PubMed 查看原文 ↗ |
| 发表日期 | 2026 |
| 作者 | Chengjian Xiao |
| 作者单位 | Department of Radiation Oncology, Ganzhou Cancer Hospital, Ganzhou 341000, People's Republic of China. |
| 期刊 | iScience |
| SCI 分区 | Q1 |
| IF | 5 |
| 研究类型 | AI/ML · 临床 |
| 所属专科 | 鼻咽癌 |
中文摘要
在鼻咽癌自适应放疗中，计划CT（计算机断层扫描）与锥形束CT（CBCT）之间的精确可变形配准至关重要，但跨模态强度差异、软组织对比度低以及CBCT伪影使对齐复杂化。我们提出NJTransMorph，一种无监督的基于Transformer的配准框架，整合了归一化梯度场损失和雅可比行列式正则化，以改善多模态结构对齐和变形合理性。NJTransMorph在内部队列（n=35）、外部扫描仪队列（n=27）和外部多中心队列（n=61）上与VoxelMorph、UTSRMorph和TransMorph进行了评估。与TransMorph相比，NJTransMorph在内部队列上将Dice分数从86.44%提高到87.35%，并将Hausdorff距离（HD95）从2.01 mm降低到1.87 mm。它还减少了外部扫描仪队列（0.27%-0.23%）和多中心队列（0.21%-0.15%）中的非正雅可比行列式。因此，在评估的深度学习方法中，NJTransMorph在扫描仪和中心变化中提高了配准精度和变形规律性。
英文摘要
Accurate deformable registration between planning CT (computed tomography) and cone-beam CT (CBCT) is essential for adaptive radiotherapy in nasopharyngeal carcinoma, but cross-modality intensity differences, low soft-tissue contrast, and CBCT artifacts complicate alignment. We propose NJTransMorph, an unsupervised transformer-based registration framework that integrates normalized gradient field loss and Jacobian determinant regularization to improve multimodal structural alignment and deformation plausibility. NJTransMorph was evaluated against VoxelMorph, UTSRMorph, and TransMorph on an internal cohort (n = 35), an external scanner cohort (n = 27), and an external multi-center cohort (n = 61). Compared with TransMorph, NJTransMorph improved Dice score from 86.44% to 87.35% and reduced Hausdorff distance (HD95) from 2.01 to 1.87 mm on the internal cohort. It also reduced non-positive Jacobian determinants on the external scanner cohort (0.27%-0.23%) and multi-center cohort (0.21%-0.15%). Thus, among the evaluated deep learning methods, NJTransMorph improved registration accuracy and deformation regularity across scanner and center shifts.