Digital pathology has become a standard in the pathology workflow due to its many benefits. These include the level of detail of the whole slide images generated and the potential immediate sharing of cases between hospitals. Recent advances in deep learning-based methods for image analysis make them of potential aid in digital pathology. However, a major limitation in developing computer-aided diagnostic systems for pathology is the lack of an intuitive and open web application for data annotation. This paper proposes a web service that efficiently provides a tool to visualize and annotate digitized histological images. In addition, to show and validate the tool, in this paper we include a use case centered on the diagnosis of spindle cell skin neoplasm for multiple annotators. A usability study of the tool is also presented, showing the feasibility of the developed tool.

翻译：数字病理学因其诸多优势已成为病理工作流程中的标准，包括生成全切片图像的精细细节以及实现病例在医疗机构间的即时共享。近年来基于深度学习的图像分析方法在数字病理学领域展现出潜在辅助价值，然而开发计算机辅助病理诊断系统的主要障碍在于缺乏直观且开放的数据标注网络应用程序。本文提出一种网络服务平台，可高效提供数字化组织学图像的可视化与标注工具。为验证该工具的有效性，本文以梭形细胞皮肤肿瘤诊断为用例，开展了多标注者协作研究。同时通过可用性研究证明了该工具的可行性。