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Fabio Martínez, Josué Ruano, Martín Gómez and Eduardo Romero
Colorectal cancer is the seventh cause of death and a relevant public health problem. This aggressive cancer is commonly identified during a routine endoscopy examination by characterizing a set of polyps that may appear along the colon and rectum. The polyps are usually described by the tissue appearance, shape, rigidity, surface irregularity, resectability, among others. In particular, the polyp size is an important index since large polyps are labeled as advanced adenomas with strong evidence that such adenomas may turn into cancer. Additionally, this index may also determine the procedure and surgical polyp management because of the bleeding risk. In some protocols, the polyp size indicates a closer surveillance, with additional genetic analyses. Currently, polyp size estimation is a challenge because several limitations such as the endoscopy camera distortions, illumination and exacerbated physiological conditions, abrupt motion and expert subjectivity. This work presents a state-of-the-art review of the current semi-automatic computational approaches for estimating the polyp size, aiming to reduce the subjectivity while exploring the gastrointestinal tract.