# Analysis of Compound Stained Cervical Cell Images Using Multi-Spectral Imaging
## 1 Introduction  
Cervical cancer is one of the most common gynecological malignant tumors all over the world, especially in developing countries [1; 2; 3]. However, in developed countries, cervical cancer cases have been significantly reduced; this is mainly attributed to developed countries having implemented effective cervical cancer screening programs [4; 5]. Several methods have been investigated for cervical cancer screening. The Bethesda system (TBS) classification and cellular DNA quantitative analysis are common screening methods for cervical cancer [6; 7]. Cytology-based screening has not been effective; therefore, other methods, such as HPV DNA testing, are increasingly being evaluated [8]. Cellular DNA quantitative analysis is an objective method of interpreting the cytopathic changes in cervical cells [9; 10]. Due to the superiority of screening for precancerous lesions, this technique could detect abnormalities before the morphology of cells is significantly changed [11; 12]. Studies have found that women screened for cervical cancer at least once in their lifetime using HPV DNA testing significantly reduce their risk of developing advanced cervical cancers and cervical-cancer-related deaths [13; 14]. There are some obstacles to implementing DNA quantitative analysis for cervical cancer screening in developing countries, such as cost, lack of infrastructure and concerns about health care workers' attitudes [15; 16]. An effective screening method is crucial for overcoming the lack of pathological resources related to cervical cancer screening in developing countries [17]. Research into cost-effective cervical cancer screening methods that involve the minimal number of clinic visits are urgently needed [18]. Multi-spectral imaging (MSI) is the technique of capturing the image data of samples within more than one wavelength; it has been widely applied in various fields such as medicine, environmental science, conservation of works of art, food, and biology [19; 20; 21; 22]. For medical detection, multi-spectral imaging has mainly been employed to analyze hidden diseases in specimens such as cells and tissues. In this regard, [PERSON] and [PERSON] used the MSI technique to measure three chromophores of the skin in the spectral range of from 500 nm to 700 nm. Experimental results showed that MSI has high sensitivity and stability in this spectral range [23]. [PERSON] et al. designed a multi-spectral camera to acquire 18 wavelength-sensitive images in a single snapshot and utilized them in order to study the characterization of skin chromophores [24]. [PERSON] et al. injected a specific mixture of fluorescent substances into the cervix of 10 patients with early cervical cancer, and fluorescent signals were detected in the lymph nodes of six patients by a real-time fluorescence spectral imaging system [25]. In general, TBS classification and cellular DNA quantitative analysis are performed separately on two different smears. It is difficult to carry out morphological analysis and DNA ploidy analysis of one cell at the same time. The compound staining method can reach the efficacy of simultaneously using the above two screening methods on the same smear [26]. In the compound-stained smears, the cytoplasm of cells is Papanicolauo-stained and the nuclei are Feulgen-stained, which leads to interference in DNA absorbance. To solve the above-mentioned issue, an absorbance-unmixing model is utilized in this study. Doctors are, therefore, able to acquire colored images of cells and the DNA index of the nucleus for each cell. This improvement can provide the possibility for doctors to perform morphological analysis and DNA ploidy analysis of cells simultaneously and efficiently, which leads to a positive effect on the accuracy of diagnosis. In this study, compared with a color camera of the same pixel size and area, each pixel from our solution could represent a different color band after using a designed interpolation algorithm to calculate the spectral image of multiple color channels.