TY - GEN
T1 - Surgical instrument segmentation based on multi-scale and multi-level feature network
AU - Wang, Yiming
AU - Qiu, Zhongxi
AU - Hu, Yan
AU - Chen, Hao
AU - Ye, Fangfu
AU - Liu, Jiang
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85122539184&partnerID=8YFLogxK
U2 - 10.1109/EMBC46164.2021.9629891
DO - 10.1109/EMBC46164.2021.9629891
M3 - Conference contribution
C2 - 34891802
AN - SCOPUS:85122539184
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 2672
EP - 2675
BT - 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
Y2 - 1 November 2021 through 5 November 2021
ER -