By Johanna Maria Ticar
The grasp thesis of Johanna Maria Ticar unearths high-resolution insights into the myocardial microstructure and illustrates that cardiac muscle fibers are instantly, working in parallel with one most popular fiber path, in spite of the fact that, deposits similar to fats appear to compromise the ordinary and compact constitution. moment harmonic iteration imaging mixed with optical tissue clearing is a correct strategy for picking out the three-d muscle fiber and sheet orientations and consequently, permits the calculation of fiber rotation during the ventricle wall.
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Additional resources for 3D Analysis of the Myocardial Microstructure: Determination of Fiber and Sheet Orientations
While preferred ﬁber directions appear red, orientations with a low ﬁber density appear blue. Hence, blue areas indicate the presence of only few to no ﬁbers. 2). From the ﬁt, both the location parameter μ and the concentration parameter b were obtained and calculated for every single image in the z-stack. The location parameter μ describes the principal (preferred) ﬁber orientation of the distribution, while the concentration parameter b determines the shape of the von Mises distribution. A narrower distribution indicates elevated b-values and hence, more aligned ﬁbers.
Previous to the actual imaging the sample was rotated 90◦ around the x-axis. (a) is an in-plane (xz) projection of the top of the volume-rendered sample. 7 depicts two different samples, both having a depth of 500 μm with a step size of 5 μm in between individual slices and in-plane dimension 620×620 μm. 14) is higher. 1 as this sample was considered to be an outlier. Although both samples have b-values above 1 (indicating highly aligned ﬁbers), the ﬁber alignment of the sample shown in (a) is superior.
Hence, while red areas show a high density of ﬁbers in the indicated direction, blue areas display orientations with a low ﬁber density. A ﬁber angle of 0◦ denotes the alignment of ﬁbers in the direction that was previously characterized as ﬁber direction and thus, corresponds to the horizontal axes of the images. Additionally, the dispersion parameter κ and R2 , a measure of the goodness of ﬁt, were determined for each distribution. A value of R2 of one indicates that the data is perfectly ﬁtted, while low values of R2 refer to a poor regression.
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