Weakly supervised segmentation for real-time surgical tool tracking

Weakly supervised segmentation for real-time surgical tool tracking

Surgical tool tracking has a variety of applications in different surgical scenarios. Electromagnetic (EM) tracking can be utilised for tool tracking, but the accuracy is often limited by magnetic interference. Vision-based methods have also been suggested; however, tracking robustness is limited by...

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Bibliographic Details
Main Authors: Eung-Joo Lee, William Plishker, Xinyang Liu, Shuvra S. Bhattacharyya, Raj Shekhar
Format: Article
Language:English
Published: Wiley 2019-10-01
Series:Healthcare Technology Letters
Subjects:
endoscopes
computer vision
learning (artificial intelligence)
surgery
image segmentation
medical image processing
medical robotics
image sequences
tracking
neural nets
annotated training data
surgical tool segmentation
laparoscopic image processing
light-weight deep segmentation network
binary segmentation mask
automatic tool segmentation
robust tool tracking
supervised segmentation
real-time surgical tool tracking
surgical scenarios
electromagnetic tracking
vision-based methods
tracking robustness
deep learning-based methods
pixel-wise training data
Online Access:https://digital-library.theiet.org/content/journals/10.1049/htl.2019.0083

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https://digital-library.theiet.org/content/journals/10.1049/htl.2019.0083

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