###### Abstract  
Colorectal polyps are critical indicators of colorectal cancer (CRC). Blue Laser Imaging and Linked Color Imaging are two modalities that allow improved visualization of the colon. In conjunction with the Blue Laser Imaging (BLI) Adenoma Serrated International Classification (BASIC) classification, endoscopists are capable of distinguishing benign and pre-malignant polyps. Despite these advancements, this classification still prevails a high misclassification rate for pre-malignant colorectal polyps. This work proposes a computer aided diagnosis (CADx) system that exploits the additional information contained in two novel imaging modalities, enabling more informative decision-making during colonoscopy. We train and benchmark six commonly used CNN architectures and compare the results with 19 endoscopists that employed the standard clinical classification model (BASIC). The proposed CADx system for classifying colorectal polyps achieves an area under the curve (AUC) of 0.97. Furthermore, we incorporate visual explanatory information together with a probability score, jointly computed from White Light, Blue Laser Imaging, and Linked Color Imaging. Our CADx system for automatic polyp malignancy classification facilitates future advances towards patient safety and may reduce time-consuming and costly histology assessment. blue light imaging; linked color imaging; colorectal polyp classification; artificial intelligence; deep learning; CADx; CNN +
Footnote †: journal: Applied  
0000-0001-5899-4000-0000-0000-0000-0000-0000-00000-00000-0000-00000-00000-00000-00000-00000-00000-00000-00000-00000-00000-00000-00000-00000-000000-00000-00  
which include the hyperplastic polyps (HP); and (2) pre-malignant CRPs, comprising adenomas (ADs) and the sessile serrated adenomas (SSAs). HPs are considered benign polyps, whilst ADs and SSAs are capable of developing into CRC when kept untreated [3]. In consequence, not all CRPs are removed, as different types of colorectal polyps lead to a different risk of progression into CRC. However, even for experienced and trained endoscopists, it is hard to differentiate between benign and pre-malignant CRPs based on their visual appearance [4]. Therefore, current medical protocols dictate that all detected colorectal polyps should be resected to undergo histological evaluation. However, this protocol has two considerable drawbacks, since (1) unnecessary removal of benign polyps exposes the patient to additional risks of polypectomy-related complications and (2) histological examination of all resected polyps leads to significantly increased costs. In order to minimize both the risk and cost, the strategy of resect-and-discard has been proposed for diminutive (\(\leq\)5 mm) adenomatous polyps [5; 6; 7] and the diagnose-and-leave strategy for diminutive hyperplastic polyps [8; 9]. In spite of the aforementioned strategies, visual differentiation of CRPs is an ongoing challenge in the clinical endoscopy routine. White light endoscopy (WL) is the most common technique for detecting lesions in the intestinal tract, but it falls behind when enhancing the visualization of the vessels and the mucosa. Compared to WL, chromoendoscopy techniques [10] are capable of achieving high-contrast results, but they require the injection of chemical dyes into the body. Similar visual effects can be achieved with the use of in-vivo optical filters, like Narrow-Band Imaging (NBI) [11; 12]. An alternative to NBI is the four-LED Multi Light Technology (Fujifilm Co.), based on the combination of four types of light as source emitters: blue-violet, blue, green, and red. Blue Light Imaging (BLI) and Linked Color Imaging (LCI) are two of the observation modes of the four-LED Multi Light Technology that allow enhanced visualization of hemoglobin. BLI intensifies the blue light emission in the range of 410 nm, which enhances the visualization of the vessels and the mucosa.