SEGMENT3D: A Web-based Application for Collaborative Segmentation of 3D images used in the Shoot Apical Meristem
This tool addresses the need for user-correctable segmentation in computational plant analysis, offering a collaborative solution for researchers in plant biology and 3D imaging.
The paper tackles the problem of cell segmentation in 3D confocal microscopy images of the shoot apical meristem, which is hindered by signal intensity variations, by proposing SEGMENT3D, a web-based collaborative application that allows interactive or correction-based segmentation of 3D tiles and automatically merges results to complete the segmentation.
The quantitative analysis of 3D confocal microscopy images of the shoot apical meristem helps understanding the growth process of some plants. Cell segmentation in these images is crucial for computational plant analysis and many automated methods have been proposed. However, variations in signal intensity across the image mitigate the effectiveness of those approaches with no easy way for user correction. We propose a web-based collaborative 3D image segmentation application, SEGMENT3D, to leverage automatic segmentation results. The image is divided into 3D tiles that can be either segmented interactively from scratch or corrected from a pre-existing segmentation. Individual segmentation results per tile are then automatically merged via consensus analysis and then stitched to complete the segmentation for the entire image stack. SEGMENT3D is a comprehensive application that can be applied to other 3D imaging modalities and general objects. It also provides an easy way to create supervised data to advance segmentation using machine learning models.