Automated overview of complete endoscopies with unsupervised learned descriptors
Barbed, O. León (Universidad de Zaragoza) ; Azagra, Pablo (Universidad de Zaragoza) ; Plo, Juan ; Murillo, Ana C. (Universidad de Zaragoza)
Resumen: Purpose
We aim to automate the initial analysis of complete endoscopy videos, identifying the sparse relevant content. This facilitates long procedure recording understanding, reduces the clinicians’ review time, and facilitates downstream tasks such as video summarization, event detection, and 3D reconstruction.
Methods
Our approach extracts endoscopic video frame representations with a learned embedding model. These descriptors are clustered to find visual patterns in the procedure, identifying key scene types (surgery, clear visibility frames, etc.) and enabling segmentation into informative and non-informative video parts.
Results
Evaluation on complete colonoscopy videos presents good performance identifying surgery segments and different visibility conditions. The method produces structured overviews that separate useful segments from irrelevant ones. We illustrate its suitability and benefits as preprocessing for other downstream tasks, such as 3D reconstruction or video summarization.
Conclusion
Our approach enables automated endoscopy overview generation, helping the clinicians focus on the relevant video content such as good visibility sections and surgery actions. The presented work facilitates faster recording reviewing for clinicians and effective video preprocessing for downstream tasks.
Idioma: Inglés
DOI: 10.1007/s11548-025-03502-1
Año: 2025
Publicado en: International Journal of Computer Assisted Radiology and Surgery (2025), [8 p.]
ISSN: 1861-6429
Financiación: info:eu-repo/grantAgreement/ES/DGA/T45-23R
Financiación: info:eu-repo/grantAgreement/EC/H2020/863146/EU/EndoMapper: Real-time mapping from endoscopic video/EndoMapper
Financiación: info:eu-repo/grantAgreement/ES/MICINN/PID2021-125514NB-I00
Tipo y forma: Article (Published version)
Área (Departamento): Área Ingen.Sistemas y Automát. (Dpto. Informát.Ingenie.Sistms.)
Área (Departamento): Área Lenguajes y Sistemas Inf. (Dpto. Informát.Ingenie.Sistms.)
You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
Exportado de SIDERAL (2025-10-17-14:13:42)
Visitas y descargas
We aim to automate the initial analysis of complete endoscopy videos, identifying the sparse relevant content. This facilitates long procedure recording understanding, reduces the clinicians’ review time, and facilitates downstream tasks such as video summarization, event detection, and 3D reconstruction.
Methods
Our approach extracts endoscopic video frame representations with a learned embedding model. These descriptors are clustered to find visual patterns in the procedure, identifying key scene types (surgery, clear visibility frames, etc.) and enabling segmentation into informative and non-informative video parts.
Results
Evaluation on complete colonoscopy videos presents good performance identifying surgery segments and different visibility conditions. The method produces structured overviews that separate useful segments from irrelevant ones. We illustrate its suitability and benefits as preprocessing for other downstream tasks, such as 3D reconstruction or video summarization.
Conclusion
Our approach enables automated endoscopy overview generation, helping the clinicians focus on the relevant video content such as good visibility sections and surgery actions. The presented work facilitates faster recording reviewing for clinicians and effective video preprocessing for downstream tasks.
Idioma: Inglés
DOI: 10.1007/s11548-025-03502-1
Año: 2025
Publicado en: International Journal of Computer Assisted Radiology and Surgery (2025), [8 p.]
ISSN: 1861-6429
Financiación: info:eu-repo/grantAgreement/ES/DGA/T45-23R
Financiación: info:eu-repo/grantAgreement/EC/H2020/863146/EU/EndoMapper: Real-time mapping from endoscopic video/EndoMapper
Financiación: info:eu-repo/grantAgreement/ES/MICINN/PID2021-125514NB-I00
Tipo y forma: Article (Published version)
Área (Departamento): Área Ingen.Sistemas y Automát. (Dpto. Informát.Ingenie.Sistms.)
Área (Departamento): Área Lenguajes y Sistemas Inf. (Dpto. Informát.Ingenie.Sistms.)
You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. Exportado de SIDERAL (2025-10-17-14:13:42)
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Este artículo se encuentra en las siguientes colecciones:
Articles > Artículos por área > Ingeniería de Sistemas y Automática
Articles > Artículos por área > Lenguajes y Sistemas Informáticos
Record created 2025-09-19, last modified 2025-10-17