Caratterizzazione fisica di apparati per tomosintesi digitale della mammella

In questo lavoro di tesi sono state studiate le caratteristiche di una macchina per tomosintesi Fujifilm AMULET Innovality in uso presso l'Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (I.R.S.T.) di Meldola. Le valutazioni sono state fatte utilizzando diversi fantocci, uno dei quali costruito durante il lavoro di tesi. Per la valutazione delle immagini di mammografia digitale e di tomosintesi sono state seguite le linee guida della International Electrotechnical Commission (IEC) e della European Reference Organisation for Quality Assured Breast Screening and Diagnostic Services (EUREF). Per lo studio delle mammografie digitali sono stati valutati, utilizzando i software COQ e ImageJ, i parametri di NPS, MTF e DQE. Per lo studio delle immagini di tomosintesi sono stati appositamente sviluppati degli algoritmi in linguaggio Java, integrati poi all'interno del software COQ. Il programma sviluppato ha permesso di valutare ASF, MTF, NPS e omogeneità delle immagini ricostruite.

Performance analysis of reconstruction algorithms for breast microwave imaging

The problem of localizing a scatterer, which represents a tumor, in a homogeneous circular domain, which represents a breast, is addressed. A breast imaging method based on microwaves is considered. The microwave imaging involves to several techniques for detecting, localizing and characterizing tumors in breast tissues. In all such methods an electromagnetic inverse scattering problem exists. For the scattering detection method, an algorithm based on a linear procedure solution, inspired by MUltiple SIgnal Classification algorithm (MUSIC) and Time Reversal method (TR), is implemented. The algorithm returns a reconstructed image of the investigation domain in which it is detected the scatterer position. This image is called pseudospectrum. A preliminary performance analysis of the algorithm vying the working frequency is performed: the resolution and the signal-to-noise ratio of the pseudospectra are improved if a multi-frequency approach is considered. The Geometrical Mean-MUSIC algorithm (GM- MUSIC) is proposed as multi-frequency method. The performance of the GMMUSIC is tested in different real life computer simulations. The performed analysis shows that the algorithm detects the scatterer until the electrical parameters of the breast are known. This is an evident limit, since, in a real life situation, the anatomy of the breast is unknown. An improvement in GM-MUSIC is proposed: the Eye-GMMUSIC algorithm. Eye-GMMUSIC algorithm needs no a priori information on the electrical parameters of the breast. It is an optimizing algorithm based on the pattern search algorithm: it searches the breast parameters which minimize the Signal-to-Clutter Mean Ratio (SCMR) in the signal. Finally, the GM-MUSIC and the Eye-GMMUSIC algorithms are tested on a microwave breast cancer detection system consisting of an dipole antenna, a Vector Network Analyzer and a novel breast phantom built at University of Bologna. The reconstruction of the experimental data confirm the GM-MUSIC ability to localize a scatterer in a homogeneous medium.