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Improved Pathology Detection in Wireless Capsule Endoscopy Images through Artificial Intelligence and 3D Reconstruction


Description:

As indicated by its title: "Improved Pathology Detection in Wireless Capsule Endoscopy Images through artificial Intelligence and 3D Reconstruction", the core concept of the project is to facilitate more accurate and efficient detection of intestinal diseases through capsule endoscopy, leading to better healthcare. The project is highly relevant and of great benefit to society. Accurate and efficient tools for diagnosis are essential in order to facilitate intestinal screening and monitoring programs for large parts of the population that seek to detect diseases at an early stage and thereby prevent severe diseases from developing. The project is divided into three work packages. The first focuses on developing more accurate and efficient automatic pathology detection algorithms than state-of-the art methods. These will also be compared to the performance of trained gastroenterologists. The second work package focuses on constructing 3D models based on wireless capsule endoscopy images that will help gastroenterologists more easily detect pathologies in the intestinal wall. The third work package is dedicated to the combination of automatic pathology detection and 3D reconstruction. The goal is twofold: i) automatically construct 3D model based on pathology detection algorithms predictions for enhanced viewing by gastroenterologists. ii) Improve automatic pathology detection using 3D data as input. The project includes one national (Innlandet Hospital) and three international partners (University of Thessaly, Sheffield Teaching Hospitals and Max Planck Institute for Informatics), whom of each is renowned in their field and highly capable of bringing complementary skills. This collaboration facilitates and enhances the value creation through the utilization of the research results in practice. It also ensures that the results are brought into practice faster and thereby benefit society.


Project leader: Marius Pedersen

Started: 2019

Ends: 2023

Category: Universiteter

Sector: UoH-sektor

Budget: 16000000

Institution: Institutt for datateknologi og informatikk

Address: Trondheim