2006
DOI: 10.1109/tuffc.2006.111
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FEMMINA real-time, radio-frequency echo-signal equipment for testing novel investigation methods

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Cited by 28 publications
(11 citation statements)
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“…Thanks to advances in spectral analyses based on wavelet decomposition of the raw radio frequency (RF) signals, tailored color maps can be developed and superimposed on conventional echographic images, in order to automatically highlight nano-sized differences in tissue [25], [26]. Exploring the applicability of this approach to NPCA-enhanced imaging we showed the possibility of automatically detecting SiNSs on echographic images with sensitivities of up to about 77% [24].…”
Section: B Automatic Segmentation Of Tissue-targeted Sinssmentioning
confidence: 99%
“…Thanks to advances in spectral analyses based on wavelet decomposition of the raw radio frequency (RF) signals, tailored color maps can be developed and superimposed on conventional echographic images, in order to automatically highlight nano-sized differences in tissue [25], [26]. Exploring the applicability of this approach to NPCA-enhanced imaging we showed the possibility of automatically detecting SiNSs on echographic images with sensitivities of up to about 77% [24].…”
Section: B Automatic Segmentation Of Tissue-targeted Sinssmentioning
confidence: 99%
“…A software for wavelet decomposition and spectral analysis (RULES, ELEN SpA, Florence, Italy) was applied to raw ultrasound signals acquired through FEMMINA, 23 and employed to develop a tailored color map then superimposed to B-mode images.…”
Section: Automatic Nanoparticle Detection Through Rf Signal Analysismentioning
confidence: 99%
“…3, a typical setup used for opto-acoustic ultrasound generation is shown. A FEMMINA (Fast Echographic Multi parameters Multi Image Novel Apparatus) system [8] is used both to acquire data and to manage hardware control and synchronization. FEMMINA is a hardware/software platform devoted to acquire, analyze and visualize in real time data produced at the same time from different sources or algorithms.…”
Section: Opto-acoustic Sourcementioning
confidence: 99%