## Materials and Methods
### Colonoscopy Database
The result indicating that patients with MC were more prone to adenoma corresponds with results reported previously [1] and indicates that even if patients with MC are more likely to exhibit polyps under colonoscopy, they have a higher adenoma incidence than other people do. MC is associated with adenomas. The study initially used a smaller quantity of data and image analysis to help determine the pattern of screening and analysis for all subsequent data. We excluded the data of patients without CEAs, poor colon preparation, or with unclear data. Finally, 370 patients were included in the image analysis study. The relationship between image texture GLCMs and CEAs was compared. Among the 370 patients, 181 had polyps and pathological biopsies. The study used images of 181 patients. All pictures collected by one gastroenterologist. Using Image J, a 100 \(\times\) 100-pixel block diagram--taken from outside areas where feces had accumulated or from positions in the centers of polyps--was isolated for analysis. Images were divided into three groups:1. Cecem, image of the appendix and cecal mucosa (C), consisting of 181 images. 2. Splenic flexure spleen images (S), consisting of 181 images. 3. Polyp (P), if the patient had a polyp or a tumor. If multiple polyps were present, we collected the largest and most prominent textured polyp. The gastroenterologist manually cut the image from central point of the polyp. This also resulted in 181 images. Figure 1a shows one melanosis coli patient's cecal image and Figure 1b shows the same patient's cecal image after stopping anthraquinone containing laxative agents for six months. This section describes the image analysis methods used in this study, like this article [17]. The way we use computer programs to analyze textures has also been widely used in other areas [18]. The images are divided into three groups as previously described. Example images of patients with MC are illustrated in Figure 2a-c and the examples of regions of interest in Figure 2d-f.  
Figure 1: Melanosis coli patient’s cecal images. (**a**) The patient took anthraquinone containing laxative medicine one year and his colonoscopy image revealed blackish mucosal pattern in colon. (**b**) The same patient’s cecal image after six months. Blackish mucosal pattern disappeared after stopping anthraquinone containing laxative agent for 6 months. Figure 2: Images extracted from one patient with melanosis coli (**a**) cecum, (**b**) splenic flexure, and (**c**) colon polyp. The regions of interest (**d**) cecum—from (**a**); (**e**) splenic flexure—from (**b**); (**f**) colon polyp—from (**c**). The images demonstrate that the MC has a particular dark brown pigmentation and presents a special black texture; places without pigmentation are white. The color textures of polyps or tumors are obviously different from the surroundings, exhibiting lighter and more turbulent textures, and most of them have no black texture. We analyze the GLCM for quantitative feature extraction and the 14 features of the GLCM. The characteristics of the study are divided into three types: pattern, brightness, and texture features. Analysis focuses mainly on the texture features, and the results are calculated using the colonoscopy image RGB channels. The method for verifying the results uses the Pearson correlation coefficient to verify the correlation between features and pathological results. The tool calculates the Pearson correlation coefficients and \(p\) values using MS Excel and IBM Statistical Package for the Social Sciences (SPSS). A Pearson correlation coefficient close to 0.4 and a \(p\) of \(<\)0.05 represent significant correlation.