Automatic two-step detection of pulmonary nodules

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F07%3A03134566" target="_blank" >RIV/68407700:21230/07:03134566 - isvavai.cz</a>

Result on the web

—

DOI - Digital Object Identifier

—

Result language

angličtina

Original language name

Automatic two-step detection of pulmonary nodules

Original language description

We present a computer-aided diagnosis (CAD) system to detect small-size (from 2mm to around 10mm) pulmonary nodules from helical CT scans. A pulmonary nodule is a small, round (parenchymal nodule) or worm (juxta-pleural) shaped lesion in the lungs. Bothhave greater radio density than lungs parenchyma. Lung nodules may indicate a lung cancer and its detection in early stage improves survival rate of patients. CT is considered to be the most accurate imaging modality for detection of nodules. However, the large amount of data per examination makes the interpretation difficult. This leads to omission of nodules by human radiologist. CAD system presented is designed to help lower the number of omissions. Our system uses two different schemes to locate juxtapleural nodules and parenchymal nodules. For juxtapleural nodules, morphological closing and thresholding is used to find nodule candidates. To locate non-pleural nodule candidates, 3D blob detector uses multiscale filtration. Ellipsoid

Czech name

Automatic two-step detection of pulmonary nodules

Czech description

We present a computer-aided diagnosis (CAD) system to detect small-size (from 2mm to around 10mm) pulmonary nodules from helical CT scans. A pulmonary nodule is a small, round (parenchymal nodule) or worm (juxta-pleural) shaped lesion in the lungs. Bothhave greater radio density than lungs parenchyma. Lung nodules may indicate a lung cancer and its detection in early stage improves survival rate of patients. CT is considered to be the most accurate imaging modality for detection of nodules. However, the large amount of data per examination makes the interpretation difficult. This leads to omission of nodules by human radiologist. CAD system presented is designed to help lower the number of omissions. Our system uses two different schemes to locate juxtapleural nodules and parenchymal nodules. For juxtapleural nodules, morphological closing and thresholding is used to find nodule candidates. To locate non-pleural nodule candidates, 3D blob detector uses multiscale filtration. Ellipsoid

Type

D - Article in proceedings

CEP classification

JD - Use of computers, robotics and its application

OECD FORD branch

—

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2007

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

SPIE 2007, Medical Imaging 2007: Computer-Aided Diagnosis

ISBN

978-0-8194-6630-3

ISSN

—

e-ISSN

—

Number of pages

12

Pages from-to

1-12

Publisher name

SPIE

Place of publication

Bellingham

Event location

San Diego, California

Event date

Feb 17, 2007

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

—