Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloA computer-aided diagnosis approach for emphysema recognition in chest radiography.
Anno di pubblicazione2013
FormatoCartaceo
Autore/iCoppini G, Miniati M, Monti S, Paterni M, Favilla R, Ferdeghini E
Affiliazioni autoriCNR IFC, Università di Firenze
Autori CNR e affiliazioni
  • MASSIMO MINIATI
  • EZIO MARIA FERDEGHINI
  • SIMONETTA MONTI
  • RICCARDO FAVILLA
  • GIUSEPPE COPPINI
  • MARCO PATERNI
Lingua/e
  • inglese
AbstractThe purpose of this work is twofold: (i) to develop a CAD system for the assessment of emphysema by digital chest radiography and (ii) to test it against CT imaging. The system is based on the analysis of the shape of lung silhouette as imaged in standard chest examination. Postero-anterior and lateral views are processed to extract the contours of the lung fields automatically. Subsequently, the shape of lung silhouettes is described by polyline approximation and the computed feature-set processed by a neural network to estimate the probability of emphysema. Images of radiographic studies from 225 patients were collected and properly annotated to build an experimental dataset named EMPH. Each patient had undergone a standard two-views chest radiography and CT for diagnostic purposes. In addition, the images (247) from JSRT dataset were used to evaluate lung segmentation in postero-anterior view. System performances were assessed by: (i) analyzing the quality of the automatic segmentation of the lung silhouette against manual tracing and (ii) measuring the capabilities of emphysema recognition. As to step i, on JSRT dataset, we obtained overlap percentage (?) 92.7±3.3%, Dice Similarity Coefficient (DSC) 95.5±3.7% and average contour distance (ACD) 1.73±0.87 mm. On EMPH dataset we had ? = 93.1±2.9%, DSC = 96.1±3.5% and ACD = 1.62±0.92 mm, for the postero-anterior view, while we had ? = 94.5± 4.6%, DSC = 91.0±6.3% and ACD = 2.22±0.86 mm, for the lateral view. As to step ii, accuracy of emphysema recognition was 95.4%, with sensitivity and specificity 94.5% and 96.1% respectively. According to experimental results our system allows reliable and inexpensive recognition of emphysema on digital chest radiography.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da63
Pagine a73
Pagine totali11
RivistaMedical engineering & physics
Attiva dal 1994
Editore: Butterworth-Heinemann, - Oxford
Paese di pubblicazione: Regno Unito
Lingua: inglese
ISSN: 1350-4533
Titolo chiave: Medical engineering & physics
Titolo proprio: Medical engineering & physics.
Titolo abbreviato: Med. eng. phys.
Titolo alternativo: Medical engineering and physics
Numero volume della rivista35
Fascicolo della rivista-
DOI10.1016/j.medengphy.2012.03.011
Verificato da refereeSì: Internazionale
Stato della pubblicazione-
Indicizzazione (in banche dati controllate)
  • Scopus (Codice:2-s2.0-84871508045)
Parole chiaveChest radiography, Emphysema, Computer-aided-diagnosis (CAD) systems, Neural networks, Lung segmentation
Link (URL, URI)http://www.sciencedirect.com/science/article/pii/S1350453312000598
Titolo parallelo-
Licenza-
Scadenza embargo-
Data di accettazione-
Note/Altre informazioni-
Strutture CNR
  • IFC — Istituto di fisiologia clinica
Moduli/Attività/Sottoprogetti CNR-
Progetti Europei-
Allegati
A computer-aided diagnosis approach for emphysema recognition in chest radiography.
Descrizione: Articolo PDF
Tipo documento: application/pdf

Dati associati a vecchie tipologie
I dati associati a vecchie tipologie non sono modificabili, derivano dal cambiamento della tipologia di prodotto e hanno solo valore storico.
Editore
  • Elsevier, Oxford (Regno Unito)