论文标题
分裂扩展了视觉变压器的应用范围 - 可变视觉变压器（VVIT）
Splitting expands the application range of Vision Transformer -- variable Vision Transformer (vViT)
论文作者
论文摘要
Vision Transformer（VIT）在计算机视觉方面取得了出色的成绩。尽管有许多基于变压器的架构从原始的VIT得出，但贴片的尺寸通常相同。这种缺点导致医疗领域的应用程序范围有限，因为在医疗领域，尺寸彼此不同的数据集；例如医疗图像，患者的个人信息，实验室测试等。为了克服这一限制，我们开发了一种新的派生类型的VIT称为可变视觉变压器（VVIT）。这项研究的目的是使用神经胶质瘤的T1加权磁共振图像（MRI）引入VVIT并将VVIT应用于放射素。在使用放射线学的神经胶质瘤患者中预测365天的生存期间，VVIT的灵敏度，特异性，准确性和AUC-ROC分别达到了0.83、0.82、0.81和0.76。 VVIT有可能立即处理不同类型的医疗信息。
Vision Transformer (ViT) has achieved outstanding results in computer vision. Although there are many Transformer-based architectures derived from the original ViT, the dimension of patches are often the same with each other. This disadvantage leads to a limited application range in the medical field because in the medical field, datasets whose dimension is different from each other; e.g. medical image, patients' personal information, laboratory test and so on. To overcome this limitation, we develop a new derived type of ViT termed variable Vision Transformer (vViT). The aim of this study is to introduce vViT and to apply vViT to radiomics using T1 weighted magnetic resonance image (MRI) of glioma. In the prediction of 365 days of survival among glioma patients using radiomics,vViT achieved 0.83, 0.82, 0.81, and 0.76 in sensitivity, specificity, accuracy, and AUC-ROC, respectively. vViT has the potential to handle different types of medical information at once.
