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Three-dimensional image registration of MR proximal femur images for the analysis of trabecular bone parameters
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10.1118/1.2977764
/content/aapm/journal/medphys/35/10/10.1118/1.2977764
http://aip.metastore.ingenta.com/content/aapm/journal/medphys/35/10/10.1118/1.2977764

Figures

Image of FIG. 1.
FIG. 1.

Representative high-spatial resolution image of the proximal femur. A rectangular parallelepiped masked the baseline image for the calculation of entropy (shown in orange). It was created by selecting a point on the first slice in which the greater trochanter appeared and last slice before the greater trochanter was no longer in view. The analysis region is outlined in red.

Image of FIG. 2.
FIG. 2.

Comparison of follow-up with registration vs follow-up without registration for the short-term study (a)–(d) and the long-term study (e)–(h). (a),(e) Subtraction of baseline and follow-up without registration. (b),(f) 3D rendering of nonregistered proximal femur surfaces. (c),(g) Subtraction of baseline and registered follow-up. (d),(h) 3D rendering of registered proximal femur surfaces (, ).

Image of FIG. 3.
FIG. 3.

Assessment of different interpolators on the four trabecular bone structure parameters analyzed for the six subjects of the short-term study. Values determined from images with a linear interpolation were significantly different , but -spline approximation and nearest neighbor interpolation did not change trabecular bone structure parameters significantly .

Image of FIG. 4.
FIG. 4.

The effects of the gray-level interpolation can be assessed visually. One of the steps in the trabecular microarchitecture quantification process is thresholding to create a binary image. The top row displays the gray-scale image and the bottom row displays the same image after thresholding. The baseline image, which served as the reference image, and registered follow-up images with linear interpolation, nearest neighbor interpolation, and -spline approximation for the final transform are shown.

Image of FIG. 5.
FIG. 5.

The improvement in coefficient of variation (CV) between baseline and follow-up due to registration (between 0.39% and 1.25%) was not statistically significant.

Image of FIG. 6.
FIG. 6.

Results of error simulations. (a) As the VOI was placed in shifted locations along the slice direction (a slice offset), the bone parameters changed up to 6.37%. (b) Within the same VOI, bone parameters have a dependence on the slice position demonstrating the trabecular structural heterogeneity in the proximal femur. The average percent change in bone parameters across a VOI is up to 15.73%.

Tables

Generic image for table
TABLE I.

The output of the registration algorithm, a transform with three translations and three rotations for the six subjects in the short-term study. The three planes are defined as Right/Left (R/L), Anterior/Posterior (A/P), and Inferior/Superior (I/S).

Generic image for table
TABLE II.

The output of the registration algorithm for the ten subjects in the long-term study.

Generic image for table
TABLE III.

The results from testing the robustness of the registration algorithm. The average, standard deviation (s.d.), and the root mean square error (RMSE) with respect to the expected output are shown. Initial misalignments of and 5°, and 10°, and and 20° were used.

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/content/aapm/journal/medphys/35/10/10.1118/1.2977764
2008-09-22
2014-04-25
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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Three-dimensional image registration of MR proximal femur images for the analysis of trabecular bone parameters
http://aip.metastore.ingenta.com/content/aapm/journal/medphys/35/10/10.1118/1.2977764
10.1118/1.2977764
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