A 3D virtual colonoscopy computer aided measurements: A new framework

We present a novel framework for computer aided measurements which supports physicians during 3D virtual colonoscopy. We propose a four steps methodology: (i) segment colon regions, (ii) search for colorectal polyps by means of a supervised neural network architecture, (iii) 3D reconstruction of polyp geometry using a synthetic model and (iv) qualitative and quantitative geometrical analysis. Doctor can graphically visualize and inspect the surface and search for irregularities. This qualitative visual support is extended with mathematical tools which computes diagnostic indicators. The proposed tool was tested with two different data sets of polyps. The proposed approach can be an effective diagnostic tool to evaluate the degree of malignancy of the cancer. Due to its generality, the presented framework can be easily extended to search for other types of cancers.