Surgical instrument segmentation based on multi-scale and multi-level feature network

Yiming Wang, Zhongxi Qiu, Yan Hu, Hao Chen, Fangfu Ye, Jiang Liu

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

Surgical instrument segmentation is critical for the field of computer-aided surgery system. Most of deep-learning based algorithms only use either multi-scale information or multi-level information, which may lead to ambiguity of semantic information. In this paper, we propose a new neural network, which extracts both multi-scale and multilevel features based on the backbone of U-net. Specifically, the cascaded and double convolutional feature pyramid is input into the U-net. Then we propose a DFP (short for Dilation Feature-Pyramid) module for decoder which extracts multi-scale and multi-level information. The proposed algorithm is evaluated on two publicly available datasets, and extensive experiments prove that the five evaluation metrics by our algorithm are superior than other comparing methods.

Original languageEnglish
Title of host publication43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2672-2675
Number of pages4
ISBN (Electronic)9781728111797
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021 - Virtual, Online, Mexico
Duration: 1 Nov 20215 Nov 2021

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
Country/TerritoryMexico
CityVirtual, Online
Period1/11/215/11/21

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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