Yassine, B;
Taylor, P;
Story, A;
(2018)
Fully automated lung segmentation from chest radiographs using SLICO superpixels.
Analog Integrated Circuits and Signal Processing
, 95
(3)
pp. 423-428.
10.1007/s10470-018-1153-1.
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Abstract
This project aims to create a computer-aided diagnosis (CAD) system that can be used to identify tuberculosis (TB) from chest radiographs (CXRs) and, in particular, to observe the progress of the disease where patients have had multiple images over a period of time. Such a CAD tool, if sufficiently automated could run in the background checking every CXR taken, regardless of whether the patient is a suspected carrier of TB. This paper outlines the first phase of the project: segmenting the lung region from a CXR. This is a challenge because of the variation in the appearance of the lung in different patients and even in images of the same patient.
| Type: |
Article
|
| Title: |
Fully automated lung segmentation from chest radiographs using SLICO superpixels |
| Open access status: |
An open access version is available from UCL Discovery |
| DOI: |
10.1007/s10470-018-1153-1 |
| Publisher version: |
https://doi.org/10.1007/s10470-018-1153-1 |
| Language: |
English |
| Additional information: |
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
| Keywords: |
Tuberculosis, Radiographs, Segmentation, SLICO, CAD |
| UCL classification: |
UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health > Epidemiology and Public Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > CHIME |
| URI: |
https://discovery-pp.ucl.ac.uk/id/eprint/10053149 |
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