ISINet: An Instance-Based Approach for Surgical Instrument Segmentation
- 29 September 2020
- book chapter
- Published by Springer Nature
- p. 595-605
Abstract
No abstract availableAll Related Versions
This publication has 24 references indexed in Scilit:
- Learning Where to Look While Tracking Instruments in Robot-Assisted Surgery2019
- Segmentation of surgical instruments in laparoscopic videos: training dataset generation and deep-learning-based framework2019
- Articulated Multi-Instrument 2-D Pose Estimation Using Fully Convolutional NetworksIEEE Transactions on Medical Imaging, 2018
- Mask R-CNN2017
- ToolNet: Holistically-nested real-time segmentation of robotic surgical tools2017
- FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks2017
- Real-Time Segmentation of Non-rigid Surgical Tools Based on Deep Learning and Tracking2017
- Deep Residual Learning for Image Recognition2016
- Detecting Surgical Tools by Modelling Local Appearance and Global ShapeIEEE Transactions on Medical Imaging, 2015
- A Naturalistic Open Source Movie for Optical Flow Evaluation2012