Using Vision Transformers for Classifying Surgical Tools in Computer Aided Surgeries
Abstract: Automated laparoscopic video analysis is essential for assisting surgeons during computer aided medical procedures. Nevertheless, it faces challenges due to complex surgical scenes and limited annotated data. Most of the existing methods for classifying surgical tools in laparoscopic surgeries rely on conventional deep learning methods such as convolutional and recurrent neural networks. This paper explores the use of pure self-attention based models-Vision Transformers for classifying both single-label (SL) and multi-label (ML) frames in Laparoscopic surgeries. The proposed SL and ML models were comprehensively evaluated on the Cholec80 surgical workflow dataset using 5-fold cross validation. Experimental results showed an excellent classification performance with a mean average precision mAP=95.8% that outperforms conventional deep learning multi-label models developed in previous studies. Our results open new avenues for further research on the use of deep transformer models for surgical tool detection in modern operating theaters.
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Erschienen in
-
Using Vision Transformers for Classifying Surgical Tools in Computer Aided Surgeries ; volume:10 ; number:4 ; year:2024 ; pages:232-235 ; extent:4
Current directions in biomedical engineering ; 10, Heft 4 (2024), 232-235 (gesamt 4)
- Urheber
- DOI
-
10.1515/cdbme-2024-2056
- URN
-
urn:nbn:de:101:1-2412181802205.276932104545
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:37 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- El Moaqet, Hisham
- Janini, Rami
- Abdulbaki Alshirbaji, Tamer
- Aldeen Jalal, Nour
- Möller, Knut
Ähnliche Objekte (12)
Classifying smoke in laparoscopic videos using SVM
Analysis of expansion within a pressure inflated section of an urethral stricture model
Using adaptive learning rate to generate adversarial images
Robustness evaluation on different training state of a CNN model
Determination of the water content of an ex vivo porcine liver
AUTOMED 2018 : automatisierungstechnische Verfahren für die Medizin
Sicherheiten im Recht der Europäischen Gemeinschaft
Dynamic emotion recognition using histogram of oriented gradients
Generative Adversarial Network for Facial Emotion Recognition: A Feasibility Study
Assistive Navigation Device for Visually Impaired—A Study on Reaction Time to Tactile Modality Stimuli
Nonlinearity of Magnetostrictive Torque Sensor under Varying External Magnetic Field Strength
Influence of temperature-dependent tissue parameters on monopolar coagulation model
Classifying smoke in laparoscopic videos using SVM
Analysis of expansion within a pressure inflated section of an urethral stricture model
Using adaptive learning rate to generate adversarial images
Robustness evaluation on different training state of a CNN model
Determination of the water content of an ex vivo porcine liver
AUTOMED 2018 : automatisierungstechnische Verfahren für die Medizin
Sicherheiten im Recht der Europäischen Gemeinschaft
Dynamic emotion recognition using histogram of oriented gradients
Generative Adversarial Network for Facial Emotion Recognition: A Feasibility Study
Assistive Navigation Device for Visually Impaired—A Study on Reaction Time to Tactile Modality Stimuli
Nonlinearity of Magnetostrictive Torque Sensor under Varying External Magnetic Field Strength
Influence of temperature-dependent tissue parameters on monopolar coagulation model
Classifying smoke in laparoscopic videos using SVM
Analysis of expansion within a pressure inflated section of an urethral stricture model
Using adaptive learning rate to generate adversarial images
Robustness evaluation on different training state of a CNN model
Determination of the water content of an ex vivo porcine liver
AUTOMED 2018 : automatisierungstechnische Verfahren für die Medizin
Sicherheiten im Recht der Europäischen Gemeinschaft
Dynamic emotion recognition using histogram of oriented gradients
Generative Adversarial Network for Facial Emotion Recognition: A Feasibility Study
Assistive Navigation Device for Visually Impaired—A Study on Reaction Time to Tactile Modality Stimuli
Nonlinearity of Magnetostrictive Torque Sensor under Varying External Magnetic Field Strength