Journal of Innovative Optical Health Sciences, Volume. 16, Issue 2, 2244003(2023)
Automated apoptosis identification in fluorescence imaging of nucleus based on histogram of oriented gradients of high-frequency wavelet coefficients
The automatic and accurate identification of apoptosis facilitates large-scale cell analysis. Most identification approaches using nucleus fluorescence imaging are based on specific morphological parameters. However, these parameters cannot completely describe nuclear morphology, thus limiting the identification accuracy of models. This paper proposes a new feature extraction method to improve the performance of the model for apoptosis identification. The proposed method uses a histogram of oriented gradient (HOG) of high-frequency wavelet coefficients to extract internal and edge texture information. The HOG vectors are classified using support vector machine. The experimental results demonstrate that the proposed feature extraction method well performs apoptosis identification, attaining
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Shutong Liu, Limei Su, Han Sun, Tongsheng Chen, Min Hu, Zhengfei Zhuang. Automated apoptosis identification in fluorescence imaging of nucleus based on histogram of oriented gradients of high-frequency wavelet coefficients[J]. Journal of Innovative Optical Health Sciences, 2023, 16(2): 2244003
Category: Research Articles
Received: Mar. 18, 2022
Accepted: Jun. 5, 2022
Published Online: Mar. 31, 2023
The Author Email: Hu Min (hmin@scnu.edu.cn), Zhuang Zhengfei (zhuangzf@scnu.edu.cn)