Stochastic frequency-domain tissue characterization: application to human spleens ‘in vivo’

Characterization of splenic structure in Hodgkin disease by using narrow-band filtration of backscattered ultrasound

“…4C) However, the increased mass of cellular tissue may act to spread the collagenous trabeculae, so that the tissue path interrogated by a given A-line has a lower probability of containing large specular scatterers than of containing fine reticulin scatterers, giving the lymphomatous spleen scattering characteristics closer to an f frequency dependency. This model is consistent with earlier studies that found that the mean scatterer spacing for splenic tissue was increased by lymphomatous involvement [13][14][15]. Another way of considering the involved spleen is that lymphomatous nodules act analogously to the polystyrene target: both may be foci with a higher frequency dependency of backscatter than surrounding structures, which may therefore appear as bright spots in narrow-band images, and increase the overall amplitude of the narrow-band-filtered backscatter.…”

Analysis of microstructural alterations of normal and pathological breast tissue in vivo using the AR cepstrum

“…Since Fellingham [6] first proposed the use of this parameter in 1979, mean scatterer spacing has been used by various investigators for tissue characterization [7][8][9][10][11][12][13][14][15][16][17][18]22]. Spectral techniques for estimating the mean scatterer spacing can be classified as power spectral density methods (PSD) [7], cepstral methods [9][10][11], and spectral redundancy techniques [12][13][14][15][16].…”

A Review of Ultrasound Tissue Characterization with Mean Scatterer Spacing

“…31 Sommer et al reported an MSS of 1.52 ± 0.14 mm for diffusely enlarged spleen patients ( n = 12), and an MSS of 1.10 ± 0.14 mm for normal human spleen in vivo ( n = 7). 33 Sommer et al reported an MSS of 1.10 ± 0.07 mm for 16 Hodgkin’s disease patients without splenic involvement, an MSS of 1.51 ± 0.28 mm for five Hodgkin’s disease patients with splenic involvement, and MSS of 1.10 ± 0.04 mm for normal human spleen in vivo ( n = 10). 32…”

“…Also, the peaks in the FT spectrum can be detected by using the autocorrelation of the frequency spectrum. 30-35 The peaks in the time domain and the cepstrum domain occur at…”

“…In this review, MSS estimation methods and applications are summarized. The MSS estimation techniques can be broadly classified into five major groups: time-domain autocorrelation based, 22-29 spectrum (frequency spectrum, 30-35 generalized spectrum, 21,36-39 and autoregressive model power spectrum 14,40 ) based, cepstrum (Fourier transform power cepstrum, 41 autoregressive model power cepstrum, 42 and complex cepstrum 43 ) based, phase statistics based, 44-47 and mathematical transformation (quadratic transformation, 48,49 Wold decomposition, 50 singular spectrum analysis, 51,52 and wavelet transformation 53-55 ) based methods. Future developments are also discussed.…”