T-cell spot test based on U-Net(PDF)
《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]
- Issue:
- 2021年第4期
- Page:
- 518-522
- Research Field:
- 医学人工智能
- Publishing date:
Info
- Title:
- T-cell spot test based on U-Net
- Author(s):
- PEI Xiaoti; L?Lin; HUANG Pengjie; CHEN Zhaoxue; LIN Yong
- School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
- Keywords:
- Keywords: T-cell spot test deep learning U-Net network image segmentation
- PACS:
- R318；TP391
- DOI:
- DOI:10.3969/j.issn.1005-202X.2021.04.022
- Abstract:
- Abstract: Aiming at the problems of weak noise resistance and high probability of missed detection in traditional image segmentation method, a T-cell spot segmentation algorithm based on U-Net model is proposed. The segmentation accuracy is effectively improved by smoothing noises through median filter, reducing background interference by graying, and taking Adam algorithm as a loss function. The experimental results show that, compared with the traditional segmentation method based on region growth, the proposed method based on U-Net increases F1 by 9% and 6% in the experiments with a small number of spots and lots of spots, which verifies its effectiveness.
Last Update: 2021-04-29