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Grant support

This work has received funding from Horizon 2020, the European Union's Framework Programme for Research and Innovation, under the grant agreement No. 860627 (CLARIFY) , the Spanish Ministry of Economy and Competitiveness through project PID2019-105142RB-C21 (AI4SKIN) and GVA through the project INNEST/2021/321 (SAMUEL) . he work of Cristian Camilo Pulgarin Ospina has been supported by the Spanish State Research Agency (PRE2020-093271) . The work of Rocio del Amor has been supported by the Spanish Ministry of Universities (FPU20/05263) . The work of J. Silva-Rodriguez was carried out during his previous position at Universitat Politecnica de Valencia.

Analysis of institutional authors

Pulgarin-Ospina, Cristian CamiloCorresponding AuthorDel Amor, RocíoAuthorNaranjo, ValeryAuthor

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February 17, 2025
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HistoColAi: An open-source web platform for collaborative digital histology image annotation with AI-driven predictive integration

Publicated to:Computer Methods And Programs In Biomedicine. 260 108577- - 2025-03-01 260(), DOI: 10.1016/j.cmpb.2024.108577

Authors: Pulgarin-Ospina, Cristian Camilo; del Amor, Rocio; Silva-Rodriguez, Julio Jose; Colomer, Adrian; Naranjo, Valery

Affiliations

ETS, Quebec City, PQ, Canada - Author
Univ Politecn Valencia, Inst Univ Invest Tecnol Centrada Humano, Valencia, Spain - Author
Valencian Grad Sch, Res Network Artificial Intelligence, ValgrAI, Valencia, Spain - Author

Abstract

Digital pathology is now a standard component of the pathology workflow, offering numerous benefits such as high-detail whole slide images and the capability for immediate case sharing between hospitals. Recent advances in deep learning-based methods for image analysis make them a potential aid in digital pathology. However, A significant challenge in developing computer-aided diagnostic systems for pathology is the lack of intuitive, open-source web applications for data annotation. This paper proposes a web service that efficiently provides a tool to visualize and annotate digitized histological images, integrating AI-driven predictive insights. While the tool is capable of handling various image formats, its primary use case is for Whole Slide Imaging (WSI) in the TIFF format, specifically tailored for histopathology applications. This innovative integration not only revolutionizes accessibility but also democratizes the utilization of complex deep-learning models for pathologists unfamiliar with such tools. Moreover, to demonstrate the effectiveness of this approach, we present a use case centered on the diagnosis of spindle cell skin neoplasm involving multiple annotators. Additionally, we conduct a usability study, showing the feasibility of the developed tool.

Keywords

Annotation toolDeep learningDigital pathologyWeb servic

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Computer Methods And Programs In Biomedicine due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2025, it was in position 35/124, thus managing to position itself as a Q1 (Primer Cuartil), in the category Engineering, Biomedical.

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-08-15:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 13.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 14 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 0.25.

Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Canada.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (Pulgarín Ospina, Cristian Camilo) and Last Author (Naranjo Ornedo, Valeriana).

the author responsible for correspondence tasks has been Pulgarín Ospina, Cristian Camilo.