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Autofocus method based on multi regions of interest window for cervical smear images

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Abstract

Autofocus methods play crucial roles in optical systems, which closely relate to the collected image quality. Due to the different focal lengths of cervical areas in smears, existing focusing approaches often result in blurry images of lymphocytes and epithelial cells, which are the keys for the cervical cancer detection. Aiming at this problem, a novel focus method based on multi regions of interest window is presented. The proposed approach applies multiple-median filter and histogram equalization for the image denoising. Multi-ROI (Region of interest) focus window consisting of image processing, selective search and BP (Back Propagation) neural network is used for the autofocus. Comprehensive analysis denotes that the proposed autofocus algorithm achieves the accuracy of 93.7% and an average focusing time (sec/mm2) of 11.89. Validation on another dataset CC proves its robustness, comparison with the recent studies shows its practical performance. The results which we obtained suggest that the proposed autofocus model based on multi-ROI window can be used effectively in scanning of cervical cell images.

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Acknowledgments

Dongyao Jia thanks the Beijing Jiaotong University for supporting this cooperative project.

Funding

Beijing Jiaotong University Technology development project(W19L00130).

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Authors and Affiliations

  1. School of Electronics and Information Engineering, Beijing Jiaotong University, No.3 Shangyuancun Haidian District, Beijing, 100044, China

    Chuanwang Zhang, Dongyao Jia, Nengkai Wu, Zhigang Guo & Hairui Ge

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  1. Chuanwang Zhang
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Correspondence to Dongyao Jia.

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Zhang, C., Jia, D., Wu, N. et al. Autofocus method based on multi regions of interest window for cervical smear images. Multimed Tools Appl 81, 18783–18805 (2022). https://doi.org/10.1007/s11042-022-12247-x

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