{rfName}
Au

Indexed in

Citations

Altmetrics

Impact on the Sustainable Development Goals (SDGs)

Analysis of institutional authors

Sun, YichunAuthorGuerrero-Lopez, AlejandroAuthorArias-Londono, Julian DAuthorGodino-Llorente, Juan ICorresponding Author

Share

April 22, 2025
Publications
>
Article
No

Automatic semantic segmentation of the osseous structures of the paranasal sinuses

Publicated to: Computerized Medical Imaging And Graphics. 123 102541- - 2025-07-01 123(), DOI: 10.1101/2024.06.21.599833

Authors:

Sun, Yichun; Guerrero-Lopez, Alejandro; Arias-Londono, Julian D; Godino-Llorente, Juan I
[+]

Affiliations

Univ Politecn Madrid, Escuela Tecn Super Ingn Telecomunicac, Madrid 28040, Spain - Author

Abstract

Endoscopic sinus and skull base surgeries require the use of precise neuronavigation techniques, which may take advantage of accurate delimitation of surrounding structures. This delimitation is critical for robotic-assisted surgery procedures to limit volumes of no resection. In this respect, an accurate segmentation of the osseous structures of the paranasal sinuses is a relevant issue to protect critical anatomic structures during these surgeries. Currently, manual segmentation of these structures is a labour-intensive task and requires wide expertise, often leading to inconsistencies. This is due to the lack of publicly available automatic models specifically tailored for the automatic delineation of the complex osseous structures of the paranasal sinuses. To address this gap, we introduce an open source dataset and a UNet SwinTR model for the segmentation of these complex structures. The initial model was trained on nine complete ex vivo CT scans of the paranasal region and then improved with semi-supervised learning techniques. When tested on an external dataset recorded under different conditions, it achieved a DICE score of 98.25 +/- 0.9. These results underscore the effectiveness of the model and its potential for broader research applications. By providing both the dataset and the model publicly available, this work aims to catalyse further research that could improve the precision of clinical interventions of endoscopic sinus and skull-based surgeries.
[+]

Keywords

AnatomAutomatic semantic segmentationCtDecent work and economic growthNavigationNeuronavigationOsseous structuresParanasal sinusesRobot-assisted surgerRobot-assisted surgeryU-net

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Computerized Medical Imaging And Graphics 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 25/212, thus managing to position itself as a Q1 (Primer Cuartil), in the category Radiology, Nuclear Medicine & Medical Imaging.

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 2025-12-21:

  • Scopus: 3
[+]

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 2025-12-21:

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: 1.
  • The number of mentions on the social network X (formerly Twitter): 1 (Altmetric).

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:

  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/91973/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 9
  • Downloads: 6
Continuing with the social impact of the work, it is important to emphasize that, due to its content, it can be assigned to the area of interest of ODS 8 - Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all, with a probability of 61% according to the mBERT algorithm developed by Aurora University.
[+]

Leadership analysis of institutional authors

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 (SUN, YICHUN) and Last Author (GODINO LLORENTE, JUAN IGNACIO).

the author responsible for correspondence tasks has been GODINO LLORENTE, JUAN IGNACIO.

[+]

Awards linked to the item

The authors thank C. Hoyos-Barcelo, G. Perez-de-Arenaza-Pozo and J. C. Puerta-Acevedo for collaborating in the manual annotation of the images. The authors gratefully acknowledge the Universidad Politecnica de Madrid for providing computing resources on the Magerit Supercomputer.This research was funded by an agreement between Comunidad de Madrid (Consejeria de Educacion, Universidades, Ciencia y Portavocia) and Universidad Politecnica de Madrid, to finance research actions on SARS-CoV-2 and COVID-19 disease with the REACT-UE resources of the European Regional Development Funds. This work was also supported by the Ministry of Economy and Competitiveness of Spain under Grants PID2021-128469OB-I00 and TED2021-131688B-I00, and by Comunidad de Madrid, Spain. Universidad Politecnica de Madrid supports J. D. Arias-Londono through a Maria Zambrano UP2021-035 grant funded by European Union-NextGenerationEU. The authors also thank the Madrid ELLIS unit (European Laboratory for Learning & Intelligent Systems) for its indirect support.
[+]