A Novel Feature Reconstruction Method for Bone Marrow Cell Classification
Huixiang Zhi, Muwei Jian, Hongyu Chen, Chunxiao Ren, Wenjing Xu, Changqun Nie, Hanjiang Luo, Xiaoguang Li · 2025
Bone Marrow Cells (BMC) play a pivotal role in maintaining human health, particularly in hematopoiesis and immunity. In this paper, we propose a novel module named Reduced Redundancy Block (RRBlock) in this paper. The fundamental principle is to retain a greater quantity of high-frequency information while eliminating less significant characteristics. In addition, the RR-Block is a plug-and-play solution that can be directly incorporated into Convolutional Neural Networks (CNNs). The experimental findings illustrate that substituting the$3 \times 3$convolutional layer in Residual Networks (ResNet) with this module leads to superior classification results. These results demonstrate an enhancement over certain up-todate models, underscoring the model's architecture efficacy.