The recent development of new gamma imagers based on scintillation array with high spatial resolution, has strongly improved the possibility of detecting sub-centimeter cancer in Scintimammography. However, Compton scattering contamination remains the main drawback since it limits the sensitivity of tumor detection. Principal component image analysis (PCA), recently introduced in scintimammographic imaging, is a data reduction technique able to represent the radiation emitted from chest, breast healthy and damaged tissues as separated images. From these images a Scintimammography can be obtained where the Compton contamination is "removed". In the present paper we compared the PCA reconstructed images with the conventional scintimammographic images resulting from the photopeak (Ph) energy window. Data coming from a clinical trial were used. For both kinds of images the tumor presence was quantified by evaluating the t-student statistics for independent sample as a measure of the signal-to-noise ratio (SNR). Since the absence of Compton scattering, the PCA reconstructed images shows a better noise suppression and allows a more reliable diagnostics in comparison with the images obtained by the photopeak energy window, reducing the trend in producing false positive.

Principal component analysis of scintimammographic images / Claudio, Bonifazzi; Cinti, Maria Nerina; DE VINCENTIS, Giuseppe; Livio, Finos; Valerio, Muzzioli; Margherita, Betti; N., Lanconelli; Agostino, Tartari; Pani, Roberto. - In: PHYSICA MEDICA. - ISSN 1120-1797. - STAMPA. - 21:1(2006), pp. 91-93. (Intervento presentato al convegno Workshop on Nuclear Radiology of Breast Cancer tenutosi a Rome, ITALY nel OCT 22-23, 2004) [10.1016/s1120-1797(06)80034-7].

Principal component analysis of scintimammographic images

CINTI, Maria Nerina;DE VINCENTIS, Giuseppe;PANI, Roberto
2006

Abstract

The recent development of new gamma imagers based on scintillation array with high spatial resolution, has strongly improved the possibility of detecting sub-centimeter cancer in Scintimammography. However, Compton scattering contamination remains the main drawback since it limits the sensitivity of tumor detection. Principal component image analysis (PCA), recently introduced in scintimammographic imaging, is a data reduction technique able to represent the radiation emitted from chest, breast healthy and damaged tissues as separated images. From these images a Scintimammography can be obtained where the Compton contamination is "removed". In the present paper we compared the PCA reconstructed images with the conventional scintimammographic images resulting from the photopeak (Ph) energy window. Data coming from a clinical trial were used. For both kinds of images the tumor presence was quantified by evaluating the t-student statistics for independent sample as a measure of the signal-to-noise ratio (SNR). Since the absence of Compton scattering, the PCA reconstructed images shows a better noise suppression and allows a more reliable diagnostics in comparison with the images obtained by the photopeak energy window, reducing the trend in producing false positive.
2006
principal component analysis; scintimammography; snr; t-student
01 Pubblicazione su rivista::01a Articolo in rivista
Principal component analysis of scintimammographic images / Claudio, Bonifazzi; Cinti, Maria Nerina; DE VINCENTIS, Giuseppe; Livio, Finos; Valerio, Muzzioli; Margherita, Betti; N., Lanconelli; Agostino, Tartari; Pani, Roberto. - In: PHYSICA MEDICA. - ISSN 1120-1797. - STAMPA. - 21:1(2006), pp. 91-93. (Intervento presentato al convegno Workshop on Nuclear Radiology of Breast Cancer tenutosi a Rome, ITALY nel OCT 22-23, 2004) [10.1016/s1120-1797(06)80034-7].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/362003
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