mlsanityData to 14 Oct 2026

Identifying Surgical Instruments in Pedagogical Cataract Surgery Videos through an Optimized Aggregation Network

arXiv 2501.02618 ↗First posted 5 Jan 2025cs.CVcited by 0

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Abstract (arXiv)

Instructional cataract surgery videos are crucial for ophthalmologists and trainees to observe surgical details repeatedly. This paper presents a deep learning model for real-time identification of surgical instruments in these videos, using a custom dataset scraped from open-access sources. Inspired by the architecture of YOLOV9, the model employs a Programmable Gradient Information (PGI) mechanism and a novel Generally-Optimized Efficient Layer Aggregation Network (Go-ELAN) to address the information bottleneck problem, enhancing Minimum Average Precision (mAP) at higher Non-Maximum Suppression Intersection over Union (NMS IoU) scores. The Go-ELAN YOLOV9 model, evaluated against YOLO v5, v7, v8, v9 vanilla, Laptool and DETR, achieves a superior mAP of 73.74 at IoU 0.5 on a dataset of 615 images with 10 instrument classes, demonstrating the effectiveness of the proposed model.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 15 of its 31 references that are in the map. First posted on arXiv 5 Jan 2025.

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15 of 31 references.

References · 15

  1. 2020End-to-End Object Detection with Transformerscited by 7,414
  2. 2018YOLOv3: An Incremental Improvementcited by 2,659
  3. 2022YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectorscited by 982
  4. 2024YOLOv9: Learning What You Want to Learn Using Programmable Gradient Informationcited by 425
  5. 2019CSPNet: A New Backbone that can Enhance Learning Capability of CNNcited by 381
  6. 2016EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videoscited by 367
  7. 2021TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-captured Scenarioscited by 83
  8. 2019Multi-Task Recurrent Convolutional Network with Correlation Loss for Surgical Video Analysiscited by 76
  9. 2018Tool Detection and Operative Skill Assessment in Surgical Videos Using Region-Based Convolutional Neural Networkscited by 57
  10. 2022SdAE: Self-distillated Masked Autoencodercited by 52
  11. 2018Weakly Supervised Convolutional LSTM Approach for Tool Tracking in Laparoscopic Videoscited by 35
  12. 2022Reversible Column Networkscited by 32
3 more
  1. 2020Detection and Localization of Robotic Tools in Robot-Assisted Surgery Videos Using Deep Neural Networks for Region Proposal and Detectioncited by 22
  2. 2017Simultaneous Recognition and Pose Estimation of Instruments in Minimally Invasive Surgerycited by 14
  3. 2023Deep Selection: A Fully Supervised Camera Selection Network for Surgery Recordingscited by 5

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