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使用图像风格迁移的荧光图像组织学模式转换

Fluorescence Image Histology Pattern Transformation Using Image Style Transfer.

作者信息

Izadyyazdanabadi Mohammadhassan, Belykh Evgenii, Zhao Xiaochun, Moreira Leandro Borba, Gandhi Sirin, Cavallo Claudio, Eschbacher Jennifer, Nakaji Peter, Preul Mark C, Yang Yezhou

机构信息

School of Computing, Informatics, and Decision System Engineering, Arizona State University, Tempe, AZ, United States.

The Loyal and Edith Davis Neurosurgery Research Laboratory, Department of Neurosurgery, St. Joseph's Hospital and Medical Center, Barrow Neurological Institute, Phoenix, AZ, United States.

出版信息

Front Oncol. 2019 Jun 25;9:519. doi: 10.3389/fonc.2019.00519. eCollection 2019.

DOI:10.3389/fonc.2019.00519
PMID:31293966
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6603166/
Abstract

Confocal laser endomicroscopy (CLE) allow on-the-fly intraoperative imaging in a discreet field of view, especially for brain tumors, rather than extracting tissue for examination with conventional light microscopy. Fluorescein sodium-driven CLE imaging is more interactive, rapid, and portable than conventional hematoxylin and eosin (H&E)-staining. However, it has several limitations: CLE images may be contaminated with artifacts (motion, red blood cells, noise), and neuropathologists are mainly trained on colorful stained histology slides like H&E while the CLE images are gray. To improve the diagnostic quality of CLE, we used a micrograph of an H&E slide from a glioma tumor biopsy and image style transfer, a neural network method for integrating the content and style of two images. This was done through minimizing the deviation of the target image from both the content (CLE) and style (H&E) images. The style transferred images were assessed and compared to conventional H&E histology by neurosurgeons and a neuropathologist who then validated the quality enhancement in 100 pairs of original and transformed images. Average reviewers' score on test images showed 84 out of 100 transformed images had fewer artifacts and more noticeable critical structures compared to their original CLE form. By providing images that are more interpretable than the original CLE images and more rapidly acquired than H&E slides, the style transfer method allows a real-time, cellular-level tissue examination using CLE technology that closely resembles the conventional appearance of H&E staining and may yield better diagnostic recognition than original CLE grayscale images.

摘要

共聚焦激光内镜检查(CLE)能够在术中对特定视野进行即时成像,特别是对于脑肿瘤,无需像传统光学显微镜那样提取组织进行检查。与传统苏木精和伊红(H&E)染色相比,荧光素钠驱动的CLE成像更具交互性、速度更快且便于携带。然而,它存在一些局限性:CLE图像可能会受到伪像(运动、红细胞、噪声)的干扰,而且神经病理学家主要是通过H&E等彩色染色组织学切片进行培训的,而CLE图像是灰色的。为了提高CLE的诊断质量,我们使用了一张来自胶质瘤肿瘤活检的H&E切片显微照片,并采用了图像风格迁移技术,这是一种用于整合两张图像内容和风格的神经网络方法。这是通过最小化目标图像与内容(CLE)和风格(H&E)图像之间的偏差来实现的。神经外科医生和一位神经病理学家对风格迁移后的图像进行了评估,并与传统H&E组织学进行了比较,然后他们在100对原始图像和转换后的图像中验证了质量提升情况。测试图像的平均评审分数显示,与原始CLE形式相比,100张转换后的图像中有84张伪像更少,关键结构更明显。通过提供比原始CLE图像更具可解释性且比H&E切片获取速度更快的图像,风格迁移方法允许使用CLE技术进行实时的细胞水平组织检查,其外观与传统H&E染色非常相似,并且可能比原始CLE灰度图像产生更好的诊断识别效果。

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