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Analysis of institutional authors

Akram, FarhanAuthorRashwan HAuthorAbdulwahab SAuthorMaaroof NAuthorRomani SAuthorPuig DAuthor
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Proceedings Paper

Retinal Optic Disc Segmentation Using Conditional Generative Adversarial Network

Publicated to:Frontiers In Artificial Intelligence And Applications. 308 373-380 - 2018-01-01 308(), DOI: 10.3233/978-1-61499-918-8-373

Authors: Singh VK; Rashwan HA; Akram F; Pandey N; Sarker MMK; Saleh A; Abdulwahab S; Maaroof N; Barrena JT; Romani S; Puig D

Affiliations

Bioinformatics Institute, A-Star, Singapore - Author
Kayakalp Hospital - Author
Universitat Rovira i Virgili - Author
University Hospital Sant Joan de Reus - Author

Abstract

© 2018 The authors and IOS Press. This paper proposed a retinal image segmentation method based on conditional Generative Adversarial Network (cGAN) to segment optic disc. The proposed model consists of two successive networks: generator and discriminator. The generator learns to map information from the observing input (i.e., retinal fundus color image), to the output (i.e., binary mask). Then, the discriminator learns as a loss function to train this mapping by comparing the ground-truth and the predicted output with observing the input image as a condition. Experiments were performed on two publicly available dataset; DRISHTI GS1 and RIM-ONE. The proposed model outperformed state-of-the-art-methods by achieving around 0.96 and 0.98 of Jaccard and Dice coefficients, respectively. Moreover, an image segmentation is performed in less than a second on recent GPU.

Keywords
Conditional generative adversarial networksDeep learningOptic disc segmentationRetinal image analysis

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Frontiers In Artificial Intelligence And Applications, Q4 Agency Scopus (SJR), its regional focus and specialization in Artificial Intelligence, give it significant recognition in a specific niche of scientific knowledge at an international level.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2025-05-26:

  • Google Scholar: 36
  • Scopus: 23
  • OpenCitations: 2
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 2025-05-26:

  • 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: 39 (PlumX).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: http://hdl.handle.net/20.500.11797/imarina4089625
Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: India; Singapore.

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 (Singh V) and Last Author (Puig Valls, Domènec Savi).