Collaborative analysis of multi-gigapixel imaging data using Cytomine

Abstract

Motivation: Collaborative analysis of massive imaging datasets is essential to enable scientific discoveries.Results: We developed Cytomine to foster active and distributed collaboration of multidisciplinary teams for large-scale image-based studies. It uses web development methodologies and machine learning in order to readily organize, explore, share and analyze (semantically and quantitatively) multi-gigapixel imaging data over the internet. We illustrate how it has been used in several biomedical applications.Availability and implementation: Cytomine (http://www.cytomine.be/) is freely available under an open-source license from http://github.com/cytomine/. A documentation wiki (http://doc.cytomine.be) and a demo server (http://demo.cytomine.be) are also available.Contact: info@cytomine.beSupplementary information: Supplementary data are available at Bioinformatics online.

Open Implementation of DICOM for Whole-Slide Microscopic Imaging

“…Finally, whole-slide images that are found to be of interest for research or education, can be exported as hierarchical TIFF directly from our Web viewer to a richer Internet application for collaborative analysis such as Cytomine (Marée et al, 2016). This would solve the "education and research" objective.…”

“…Currently, digital imaging starts to replace traditional glass slides and high quality microscopes to discuss interesting cases during lessons, symposia and conferences. Telepathology facilitates interactions between multiple users and allows the consistency and longevity of imaged materials (Marée et al, 2016).…”

“…The OpenSlide software can already serve whole-slide images generated by commonplace scanners onto the Web (Goode et al, 2013). Similarly, the Cytomine software builds upon the OpenSlide experience to provide an advanced collaborative analysis framework for research and education in digital pathology (Marée et al, 2016). Unfortunately, neither of those platforms currently supports the DICOM standard that is mandatory for clinical workflow.…”

An approach for detection of glomeruli in multisite digital pathology

“…Cytomine is an open-source rich internet application for collaborative analysis of large images [12]. Through HTTP transfers, we centralize images on a Cytomine server and organize them into a project with a user-defined vocabulary of terms describing renal tissue structures.…”

“…It requires softwares and algorithms able to organize persistently in databases large sets of digital slides from multiple centers, allow semantic annotation of digital slides by experts, as well as protocols and user interfaces to visualize and evaluate algorithm results. In this work we propose to combine and extend softwares (namely Cytomine 1 [12] and Icy 2 [2]), and their algorithms (based on machine learning and image processing, respectively) to enable multisite digital pathology studies.…”