用基于探针的共聚焦激光内镜视频筛查BARRETT食管。

J Vince Pulido, Shan Guleria, Lubaina Ehsan, Tilak Shah, Sana Syed, Don E Brown
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引用次数: 3

摘要

通过基于探针的共聚焦激光内镜(pCLE)对巴雷特食管和食管恶性肿瘤进行组织学诊断,可以实时检查上皮结构和靶向活检采样。尽管pCLE显示出高特异性,但敏感性仍然很低。本研究采用深度学习架构,以提高pCLE诊断食管癌症及其前体的准确性。pCLE视频被策划并注释为属于三类之一:鳞状、巴雷特氏(无发育不良的肠化生)或发育不良。我们介绍了两种新颖的视频架构,AttentionPooling和Multi-Module AttentionPoolingDeep Network,它们优于其他模型,并具有高度的可解释性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SCREENING FOR BARRETT'S ESOPHAGUS WITH PROBE-BASED CONFOCAL LASER ENDOMICROSCOPY VIDEOS.

Histologic diagnosis of Barrett's esophagus and esophageal malignancy via probe-based confocal laser endomicroscopy (pCLE) allows for real-time examination of epithelial architecture and targeted biopsy sampling. Although pCLE demonstrates high specificity, sensitivity remains low. This study employs deep learning architectures in order to improve the accuracy of pCLE in diagnosing esophageal cancer and its precursors. pCLE videos are curated and annotated as belonging to one of the three classes: squamous, Barrett's (intestinal metaplasia without dysplasia), or dysplasia. We introduce two novel video architectures, AttentionPooling and Multi-Module AttentionPooling deep networks, that outperform other models and demonstrate a high degree of explainability.

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