MT-FiST: a multi-task fine-grained spatial-temporal framework for surgical action triplet recognition

Y Li, T Xia, H Luo, B He, F Jia - IEEE journal of biomedical and …, 2023 - ieeexplore.ieee.org
Surgical action triplet recognition plays a significant role in helping surgeons facilitate scene
analysis and decision-making in computer-assisted surgeries. Compared to traditional …

Surgical tool classification and localization: results and methods from the MICCAI 2022 SurgToolLoc challenge

A Zia, K Bhattacharyya, X Liu, M Berniker… - arXiv preprint arXiv …, 2023 - arxiv.org
The ability to automatically detect and track surgical instruments in endoscopic videos can
enable transformational interventions. Assessing surgical performance and efficiency …

Analysing multi-perspective patient-related data during laparoscopic gynaecology procedures

NA Jalal, T Abdulbaki Alshirbaji, B Laufer… - Scientific reports, 2023 - nature.com
Fusing data from different medical perspectives inside the operating room (OR) sets the
stage for developing intelligent context-aware systems. These systems aim to promote better …

Laparoscopic video analysis using temporal, attention, and multi-feature fusion based-approaches

NA Jalal, TA Alshirbaji, PD Docherty, H Arabian… - Sensors, 2023 - mdpi.com
Adapting intelligent context-aware systems (CAS) to future operating rooms (OR) aims to
improve situational awareness and provide surgical decision support systems to medical …

Robustness of convolutional neural networks for surgical tool classification in laparoscopic videos from multiple sources and of multiple types: A systematic evaluation

T Abdulbaki Alshirbaji, NA Jalal, PD Docherty… - Electronics, 2022 - mdpi.com
Deep learning approaches have been explored for surgical tool classification in
laparoscopic videos. Convolutional neural networks (CNN) are prominent among the …

A comprehensive survey on recent deep learning-based methods applied to surgical data

M Ali, RMG Pena, GO Ruiz, S Ali - arXiv preprint arXiv:2209.01435, 2022 - arxiv.org
Minimally invasive surgery is highly operator dependant with a lengthy procedural time
causing fatigue to surgeon and risks to patients such as injury to organs, infection, bleeding …

Surgivisor: Transformer-based semi-supervised instrument segmentation for endoscopic surgery

Z Wu, CY Lau, Q Zhou, J Wu, Y Wang, Q Liu… - … Signal Processing and …, 2024 - Elsevier
Precise instrument segmentation helps tracking of instruments in surgery. The most of the
existing instrument segmentation methods are fully supervised, which are based on 100 …

P-CSEM: An Attention Module for Improved Laparoscopic Surgical Tool Detection

H Arabian, T Abdulbaki Alshirbaji, NA Jalal… - Sensors, 2023 - mdpi.com
Minimal invasive surgery, more specifically laparoscopic surgery, is an active topic in the
field of research. The collaboration between surgeons and new technologies aims to …

A deep learning framework for recognising surgical phases in laparoscopic videos

NA Jalal, TA Alshirbaji, PD Docherty, T Neumuth… - IFAC-PapersOnLine, 2021 - Elsevier
Image-based surgical phase recognition is a fundamental component for developing context-
aware systems in future operating rooms (ORs) and thus enhance patient outcomes. To …

Future Perspectives of Deep Learning in Laparoscopic Tool Detection, Classification, and Segmentation: A Systematic Review

N Fernandes, E Oliveira… - 2023 IEEE 11th …, 2023 - ieeexplore.ieee.org
Background—Classification, detection, and segmentation of minimally invasive instruments
is an essential component for robotic-assisted surgeries and surgical skill assessments …