LNDetector

About the Project

Automatic Detection, Segmentation and Classification of Pulmonary Nodules System in Computed Tomography Images

The goal of project LNDetector is to automatically detect, segment and classify nodules in chest CT scans. The idea is to create a working prototype of a Computer-aided diagnosis (CAD) system for lung nodule diagnosis to be installed in a radiology department. The prototype includes three main modules for nodule detection, segmentation and diagnosis. Furthermore, an anonymised and annotated CT image database will be created with a large diversity of nodules with different sizes, positions, shapes and texture features. The joint collaborative research with a major Radiology Department creates an excellent cooperation opportunity between Engineering and Medicine.

Acronym

LNDetector

Responsible

Aurélio Campilho

Status

Closed

Starting Date

January 1, 2016

Ending Date

January 30, 2019

Effective End Date

January 30, 2019

Global Budget

€198,189.00

Funding

€164,589.00

Website

Datasheet

Members

Team Leaders

Aurélio Campilho

Team Members

Ana Maria Mendonça

Aurélio Campilho

João Manuel Pedrosa

Associated Centres

Biomedical Engineering Research

The impact that science and innovation can have on the prevention, early detection, and support for the diagnosis of various types of diseases is fully explored at our Centre for Biomedical Engineering Research (C-BER). Guided by an interdisciplinary approach that prioritises technology transfer with economic impact—through the creation of new systems, tools, and methods related to disease diagnosis and monitoring, ageing, human rehabilitation, physiotherapy, and functional assessment—our researchers are dedicated to developing advanced technologies positioned at the intersection of engineering, medicine and health, and general well-being. Promoting strategic partnerships with clinical partners, research institutes, and encouraging international cooperation is one of the centre’s key priorities. Its research is structured across three distinct areas: Biomedical Imaging, Bioinstrumentation, and Neuroengineering.