Computer-aided diagnosis system for lung-related pathology

Principal Investigator

Name
Aurélio Campilho

Degrees
Ph.D.

Institution
INESC TEC - Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência

Position Title
Professor

Email
campilho@fe.up.pt

About this CDAS Project

Study
NLST (Learn more about this study)

Project ID
NLST-375

Initial CDAS Request Approval
Nov 15, 2017

Title
Computer-aided diagnosis system for lung-related pathology

Summary
The fields of computer vision and machine learning have contributed, for many years, to the development of diagnosis-aiding and second opinion systems for medical practice. One of the major issues, however, is that highly complexity of medical tasks, such as lung cancer screening, inhibits the application of most of these methods in real clinical practice.
The advances on computational power over the last few years have enabled the usage of high performing methods, such as deep learning, and thus increased the possibility of the development of reliable tools for medical practice. Since these methods require high amounts of data to develop, the NLST images and metadata may prove essential to achieve this goal.
The project aims at the development of machine-learning approaches that provide a second-opinion to clinicians during the diagnosis of lung-related pathologies, namely lung cancer. The NLST data will be used for the development and partial validation of the system.

Aims

Aims
1) Development of a system capable of detecting abnormalities on lung tissue, with special focus on the detection of lung nodules in CT images;
2) Development of a system that, given a set of abnormalities, properly predicts necessary patient follow-up;

Collaborators

All members of the CBER-Bioimaging Lab research group (www.bioimglab.inesctec.pt), namely: António Cunha, PhD; Guilherme Aresta, PhD student