JACIII Vol.26 No.2 pp. 178-187
doi: 10.20965/jaciii.2022.p0178


Enhancement of the Individual Selectness Using Local Spatial Weighting for Immune Cells

Shoya Kusunose*, Yuki Shinomiya*, Takashi Ushiwaka**, Nagamasa Maeda***, and Yukinobu Hoshino*

*Kochi Unversity of Technology
185 Miyanokuchi, Tosayamada, Kami, Kochi 782-8502, Japan

**Kagoshima University
8-35-1 Sakuragaoka, Kagoshima, Kagoshima 890-8544, Japan

***Kochi Medical School
Kohasu, Oko-cho, Nankoku, Kochi 783-8505, Japan

August 31, 2021
January 24, 2022
March 20, 2022
neural networks, image processing, individual selectness, immune cells, visualization
Enhancement of the Individual Selectness Using Local Spatial Weighting for Immune Cells

Proposal approach: Dynamic weighting, like activation mappings, is to weight RFS instead of Gaussian distribution. The weighting should be suitable for each patch image. It is possible to set the weight uniquely and suitably for each patch

This paper focuses on the analysis of the activity of immune cells for supporting medical workers. Recognition frequency space selects a region including neighboring multiple cells as a single cell is one of the major issues in activity analysis of immune cells. This study focuses on the locality of immune cell features and uses a high-velocity weighting method for the analysis while the Gaussian distribution is used in the literature. The analysis was conducted for a few well-known methods such as final feature maps, class activation mapping (CAM), gradient weighted class activation mapping (Grad-CAM), Grad-CAM++, and Eigen-CAM. The results show that the densely inhabited immune cells are correctly selected by CAM, Grad-CAM, Grad-CAM++, and Eigen-CAM. These algorithms also show stability with respect to the threshold used to select tracking targets. In addition, the higher threshold makes the selection robust, and the lower one is useful for analyzing tends of multiple cells in a whole frame efficiently.

Cite this article as:
Shoya Kusunose, Yuki Shinomiya, Takashi Ushiwaka, Nagamasa Maeda, and Yukinobu Hoshino, “Enhancement of the Individual Selectness Using Local Spatial Weighting for Immune Cells,” J. Adv. Comput. Intell. Intell. Inform., Vol.26, No.2, pp. 178-187, 2022.
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Last updated on May. 20, 2022