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A molecular atlas of the human lung is important to inform basic mechanisms and treatments for lung diseases, and imaging data provide us the foundation upon which to build the lung atlas. For analyzing immunofluorescent confocal images, annotations describing precise anatomical structures are necessary. However, it is hard to annotate increasing images manually. Thus, this study aims to develop an automatic annotation system as a combination of automatic region detection and automatic structure classification modules. As an important and first step to achieving the aim, we developed an efficient annotation data collection tool that will be used collected data to develop the automatic annotation system for the lung atlas. We describe the details of our web based annotation tool that is web based and includes user control.

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