论文标题
在治疗后恶性神经胶质瘤的患者中，置信度引导的病变面膜同时合成解剖和分子MR图像
Confidence-guided Lesion Mask-based Simultaneous Synthesis of Anatomic and Molecular MR Images in Patients with Post-treatment Malignant Gliomas
论文作者
论文摘要
数据驱动的自动方法证明了它们在解决神经肿瘤学的各种临床诊断困境方面的巨大潜力，尤其是在标准解剖和晚期分子MR图像的帮助下。但是，数据数量和质量仍然是此类应用的潜力的关键决定因素，并且是显着限制。在我们先前的工作中，我们探讨了治疗后恶性肿瘤患者的解剖学和分子MR图像网络（SAMR）的合成。 Now, we extend it and propose Confidence Guided SAMR (CG-SAMR) that synthesizes data from lesion information to multi-modal anatomic sequences, including T1-weighted (T1w), gadolinium enhanced T1w (Gd-T1w), T2-weighted (T2w), and fluid-attenuated inversion recovery (FLAIR), and the molecular amide proton transfer-weighted （APTW）序列。我们引入了一个模块，该模块基于对中间结果的置信度度量来指导合成。此外，我们将提出的架构扩展到无监督的合成，以便可以使用未配对的数据来培训网络。对实际临床数据的广泛实验表明，所提出的模型可以比最先进的合成方法更好。
Data-driven automatic approaches have demonstrated their great potential in resolving various clinical diagnostic dilemmas in neuro-oncology, especially with the help of standard anatomic and advanced molecular MR images. However, data quantity and quality remain a key determinant of, and a significant limit on, the potential of such applications. In our previous work, we explored synthesis of anatomic and molecular MR image network (SAMR) in patients with post-treatment malignant glioms. Now, we extend it and propose Confidence Guided SAMR (CG-SAMR) that synthesizes data from lesion information to multi-modal anatomic sequences, including T1-weighted (T1w), gadolinium enhanced T1w (Gd-T1w), T2-weighted (T2w), and fluid-attenuated inversion recovery (FLAIR), and the molecular amide proton transfer-weighted (APTw) sequence. We introduce a module which guides the synthesis based on confidence measure about the intermediate results. Furthermore, we extend the proposed architecture for unsupervised synthesis so that unpaired data can be used for training the network. Extensive experiments on real clinical data demonstrate that the proposed model can perform better than the state-of-theart synthesis methods.
