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Images of the stained matrix were acquired using a digital camera.
In the present study transversal slices with a thickness of 1.5 mm and 1024-image matrix were acquired, which resulted in high-resolution images.
One soft tissue series using a low frequency filter (512 × 512 image matrix) and one series for bony details using an edge enhancing filter (1024 × 1024 image matrix) were acquired.
Seven hundred and four T2*-weighted single-shot gradient-echo echo-planar images (EPI; TE/TR 40/3,000, flip angle: 90°, 21 interleaved 5 mm thick slices, FOV = 24 × 24 cm, 64 matrix) were acquired continuously over 35 min on a 1.5 Tesla Horizon EchoSpeed MRI scanner (General Electric, Milwaukee).
Seven hundred and four T2*-weighted single-shot gradient-echo echo-planar images (EPI; TE/TR: 40/3000, flip angle: 90°, 21 5 mm interleaved slices, FOV = 24 × 24 cm, 64 matrix) were acquired continuously over 35 min on a 1.5 Tesla Horizon EchoSpeed MRI scanner (General Electric, Milwaukee, WI).
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Consequently, the weighted complementary judgment matrix is acquired, as illustrated in Table 4.
By ascertaining consistency of the pairwise comparison matrixes, logarithmic least square (LLS) nonlinear programming model for each matrix is acquired.
According to MC, such a recovery is possible provided the matrix is characterized by a small rank (compared to its dimensions) and enough randomly selected entries of the matrix are acquired [6, 41].
Candès and Tao showed that under certain conditions the nuclear norm minimization in Eq. (5) can estimate the same matrix as the rank minimization in Eq. (3) with high probability provided q≥C K 6/5 r l o g(K) randomly selected entries of the rank r matrix are acquired [7] (assuming K≥L).
After an initial localizer scan, a high resolution T1-weighted MPRAGE3D anatomical image (TR/TE = 8.0/4.3 ms, flip angle = 18°, FOV = 250×250×150 mm, 256×256×168 matrix) was acquired for anatomical registration.
After removing less correlated sets of genes or the least correlated condition in a repeated way until the average correlation coefficient of the matrix is equal to or greater than the correlation threshold, a correlation-based bicluster matrix is acquired.
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