At present, mammography is the most effective examination for an early diagnosis of breast cancer. Nevertheless, the detection of cancer signs in mammograms is a difficult procedure owing to the great number of non-pathological structures which are also present in the image. Recent statistics show that in current breast cancer screenings 10%-25% of the tumors are missed by the radiologists. For this reason, a lot of research is currently being done to develop systems for Computer Aided Detection (CADe). Probably, some causes of the false-negative screening examinations are that tumoral masses have varying dimension and irregular shape, their borders are often ill-defined and their contrast is very low, thus making difficult the discrimination from parenchymal structures. Therefore, in a CADe system a preliminary segmentation procedure has to be implemented in order to separate the mass from the background tissue. In this way, various characteristics of the segmented mass can be evaluated and used in a classification step to discriminate benign and malignant cases. In this paper, we describe an effective algorithm for massive lesions segmentation based on a region-growing technique and we provide full details the performance evaluation procedure used in this specific context.

Rabottino, G., Mencattini, A., Salmeri, M., Caselli, F., Lojacono, R. (2011). Performance evaluation of a region growing procedure for mammographic breast lesion identification. COMPUTER STANDARDS & INTERFACES, 33(2), 128-135 [10.1016/j.csi.2010.06.003].

Performance evaluation of a region growing procedure for mammographic breast lesion identification

MENCATTINI, ARIANNA;SALMERI, MARCELLO;CASELLI, FEDERICA;LOJACONO, ROBERTO
2011-02-01

Abstract

At present, mammography is the most effective examination for an early diagnosis of breast cancer. Nevertheless, the detection of cancer signs in mammograms is a difficult procedure owing to the great number of non-pathological structures which are also present in the image. Recent statistics show that in current breast cancer screenings 10%-25% of the tumors are missed by the radiologists. For this reason, a lot of research is currently being done to develop systems for Computer Aided Detection (CADe). Probably, some causes of the false-negative screening examinations are that tumoral masses have varying dimension and irregular shape, their borders are often ill-defined and their contrast is very low, thus making difficult the discrimination from parenchymal structures. Therefore, in a CADe system a preliminary segmentation procedure has to be implemented in order to separate the mass from the background tissue. In this way, various characteristics of the segmented mass can be evaluated and used in a classification step to discriminate benign and malignant cases. In this paper, we describe an effective algorithm for massive lesions segmentation based on a region-growing technique and we provide full details the performance evaluation procedure used in this specific context.
feb-2011
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore ING-INF/07 - MISURE ELETTRICHE ED ELETTRONICHE
English
Con Impact Factor ISI
breast cancer; breast cancer screening; breast lesion; computer aided detection; early diagnosis; effective algorithms; irregular shape; mammographic; pathological structures; performance evaluation; region growing; region-growing techniques; segmentation procedure
Rabottino, G., Mencattini, A., Salmeri, M., Caselli, F., Lojacono, R. (2011). Performance evaluation of a region growing procedure for mammographic breast lesion identification. COMPUTER STANDARDS & INTERFACES, 33(2), 128-135 [10.1016/j.csi.2010.06.003].
Rabottino, G; Mencattini, A; Salmeri, M; Caselli, F; Lojacono, R
Articolo su rivista
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S0920548910000814-main.pdf

solo utenti autorizzati

Descrizione: articolo su rivista
Licenza: Copyright dell'editore
Dimensione 1.56 MB
Formato Adobe PDF
1.56 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/12959
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 25
  • ???jsp.display-item.citation.isi??? 19
social impact