Instance segmentation of low contrast and high density cell images using mask R-CNN

Hejun Huang; Zuguo Chen

doi:10.1117/12.2627206

14 February 2022 Instance segmentation of low contrast and high density cell images using mask R-CNN

Hejun Huang, Zuguo Chen

Proceedings Volume 12161, 4th International Conference on Informatics Engineering & Information Science (ICIEIS2021); 1216111 (2022) https://doi.org/10.1117/12.2627206
Event: 4th International Conference on Informatics Engineering and Information Science, 2021, Tianjin, China

Abstract

The light microscope image of glioblastoma cell line A172 has the characteristics of low contrast and high density. An improved algorithm based on Mask R-CNN is proposed. The residual neural network of this algorithm is introduced into deformable convolution to enhance the segmentation ability of multi-cell shapes, and at the same time, based on the feature pyramid network, the high-level semantic structure information is transferred to the bottom layer to form dense connections to adapt to the detection of dense feature images. This instance segmentation algorithm has been verified in the human glioblastoma A172 cell line in the LIVECell-2021 data set. Comparative experiments show that our method performs better in COCO evaluation indicators and visual segmentation effects. Among them, in terms of detection performance, AP increased by 0.319%, AP50 increased by 0.107%, and AP50 increased by 0.136% in segmentation performance.

Citation Download Citation

Hejun Huang and Zuguo Chen "Instance segmentation of low contrast and high density cell images using mask R-CNN", Proc. SPIE 12161, 4th International Conference on Informatics Engineering & Information Science (ICIEIS2021), 1216111 (14 February 2022); https://doi.org/10.1117/12.2627206

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available