Lesion Mask-Based Simultaneous Synthesis of Anatomic and Molecular MR Images Using a GAN.
Lesion Mask-Based Simultaneous Synthesis of Anatomic and Molecular MR Images Using a GAN.
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DOI：
10.1007/978-3-030-59713-9_11
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发表时间：
2020-10
期刊：
影响因子：
--
通讯作者：
Jiang S
中科院分区：
文献类型：
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作者：
Guo P;Wang P;Zhou J;Patel VM;Jiang S
数据驱动的自动方法已经证明了它们在解决神经肿瘤学中恶性胶质瘤患者的各种临床诊断困境方面的巨大潜力，这些患者可以借助常规和先进的分子MR图像。然而，缺乏足够的注释MRI数据极大地阻碍了此类自动方法的开发。传统的数据增强方法，包括翻转、缩放、旋转和失真，不能生成具有不同图像内容的数据。在本文中，我们提出了一种方法，称为合成的解剖和分子MR图像网络（SAMR），它可以同时合成的数据从任意处理的病变信息的多个解剖和分子MRI序列，包括T1加权（T1 w），钆增强T1 w（Gd-T1 w），T2加权（T2 w），液体衰减反转恢复（FLAIR），和酰胺质子转移加权（APTw）。该框架包括一个扩展的上采样模块，大脑图谱编码器，分割一致性模块，和多尺度标签式鉴别器。在真实的临床数据上的大量实验表明，该模型的性能明显优于最先进的合成方法。
Data-driven automatic approaches have demonstrated their great potential in resolving various clinical diagnostic dilemmas for patients with malignant gliomas in neuro-oncology with the help of conventional and advanced molecular MR images. However, the lack of sufficient annotated MRI data has vastly impeded the development of such automatic methods. Conventional data augmentation approaches, including flipping, scaling, rotation, and distortion are not capable of generating data with diverse image content. In this paper, we propose a method, called synthesis of anatomic and molecular MR images network (SAMR), which can simultaneously synthesize data from arbitrary manipulated lesion information on multiple anatomic and molecular MRI sequences, including T1-weighted (T1w), gadolinium enhanced T1w (Gd-T1w), T2-weighted (T2w), fluid-attenuated inversion recovery (FLAIR), and amide proton transfer-weighted (APTw). The proposed framework consists of a stretch-out up-sampling module, a brain atlas encoder, a segmentation consistency module, and multi-scale label-wise discriminators. Extensive experiments on real clinical data demonstrate that the proposed model can perform significantly better than the state-of-the-art synthesis methods.