Cloud Based Digital Pathology

We developed a cloud-based end-user tool for large scale digital pathology WSI visualization, training deep learning models for detection and segmentation of tissue micro-compartments, and quantification of relevant structures. The tool is made available for the community via our cloud-based instance – HistoCloud. The source codedocker image, and a video overview of the tool are made freely available for the community.

The user interface of HistoCloud. 
The user interface of HistoCloud. 

Select References

B. Lutnick, D. Manthey, J. U. Becker, B. Ginley, K. Moos, J. E. Zuckerman, L. Rodrigues, A. J. Gallan, L. Barisoni, C. E. Alpers, X. X. Wang, K. Myakala, B. A. Jones, M. Levi, J. B. Kopp, T. Yoshida, S. S. Han, S. Jain, A. Z. Rosenberg, K. Y. Jen, and P. Sarder, for the Kidney Precision Medicine Project, “A user-friendly tool for cloud-based whole slide image segmentation, with examples from renal histopathology,” Communications Medicine (London), vol. 2, pp. 105: 1-15, Aug. 2022.

Underline indicates corresponding author.
* indicates equal contribution.
indicates Dr. Sarder’s faculty trainees.
§ indicates post doctoral associates.
indicates Dr. Sarder’s graduate students.
indicates Dr. Sarder’s undergraduate students.