X-Balloon: A cloud-based platform for annotation and reinforced deep learning in digital pathology images

This paper introduces X-Balloon, a cloud-based platform designed to streamline annotation workflows and reinforce deep learning models specifically for biopsy or digital pathology image analysis. The platform integrates a modular architecture comprising a Backend, Annotation, and AI Processing module to address inefficiencies in traditional pathology workflows. By leveraging Mask R-CNN for automated segmentation, X-Balloon achieves high precision in identifying pathological features, thereby enhancing diagnostic accuracy. Its browser-based interface enables seamless collaboration among pathologists while reducing annotation effort through a combination of automation and manual refinement. X-Balloon’s open-source availability and customizable architecture make it a valuable tool for advancing the integration of AI into digital pathology.

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Publication Details

Journal
SoftwareX
Published
2025-07-24
DOI
https://doi.org/10.1016/j.softx.2025.102287
Primary Topic
AI in cancer detection
Type
article
Field-Weighted Citation Impact
0.00

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article

X-Balloon: A cloud-based platform for annotation and reinforced deep learning in digital pathology images

Alexandros T. Tzallas, Νικόλαος Γιαννακέας, Ανδρέας Μιλτιάδους, Odysseas Tsakai et al.
1 links
SoftwareX
AI in cancer detection
article

X-Balloon: A cloud-based platform for annotation and reinforced deep learning in digital pathology images

Alexandros T. Tzallas, Νικόλαος Γιαννακέας, Ανδρέας Μιλτιάδους, Odysseas Tsakai, Markos G. Tsipouras, Panagiotis N. Smyrlis
article en

Abstract

This paper introduces X-Balloon, a cloud-based platform designed to streamline annotation workflows and reinforce deep learning models specifically for biopsy or digital pathology image analysis. The platform integrates a modular architecture comprising a Backend, Annotation, and AI Processing module to address inefficiencies in traditional pathology workflows. By leveraging Mask R-CNN for automated segmentation, X-Balloon achieves high precision in identifying pathological features, thereby enhancing diagnostic accuracy. Its browser-based interface enables seamless collaboration among pathologists while reducing annotation effort through a combination of automation and manual refinement. X-Balloon’s open-source availability and customizable architecture make it a valuable tool for advancing the integration of AI into digital pathology.

SoftwareXVol. 31
University of Ioannina (GR), University of Western Macedonia (GR)
European Commission
Openalex Percentile: Top 91%
AI in cancer detection
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