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Detecting microvascular changes in the mouse spleen using optical computed tomography.

McErlean CM, Boult JK, Collins DJ, Leach MO, Robinson SP, Doran SJ - Microvasc. Res. (2015)

Bottom Line: A significant difference in total splenic volume was found between vehicle and ZD6126-treated cohorts, with mean volumes of 61±3mm(3) and 44±3mm(3) respectively (both n=3, p=0.05).Textural statistics for each sample were calculated using grey-level co-occurrence matrices (GLCMs).Standard 2-D GLCM analysis was found to be slice-dependent while 3-D GLCM contrast and homogeneity analysis resulted in separation of the vehicle and ZD6126-treated cohorts over a range of length scales.

View Article: PubMed Central - PubMed

Affiliation: Cancer Research UK Cancer Imaging Centre, The Institute of Cancer Research, Sutton SM2 5NG, UK. Electronic address: cmcerlean@icr.ac.uk.

No MeSH data available.


Related in: MedlinePlus

a. and b. Orthogonal cross-section slices of a reconstructed ZD6126-treated spleen image volume from Dataset 2 with FOV (5.3 mm)3. The yellow boxes indicate the position of the region-of-interest (ROI) (size 200 × 200 × 30 pixels) chosen for textural feature analysis. ROIs for the other samples were chosen to be in similar positions with respect to spleen boundaries. c. Representation of the four angular pixel directions used in grey level co-occurrence matrix (GLCM) calculations. For each pixel displacement, d, GLCMs were calculated in each angular direction and averaged to give one GLCM per displacement distance. d. Demonstration of the relative positions of three reference pixels used in 3-D GLCM calculations for the case of d = 2 and θ = 45°. For 2-D GLCM calculations only pixels i and j were compared. 3-D GLCM analysis incorporates depth information by including a third reference pixel, k, in the z direction. Pixel position changes Δx, Δy and Δz can be calculated from Eq. (1).
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f0015: a. and b. Orthogonal cross-section slices of a reconstructed ZD6126-treated spleen image volume from Dataset 2 with FOV (5.3 mm)3. The yellow boxes indicate the position of the region-of-interest (ROI) (size 200 × 200 × 30 pixels) chosen for textural feature analysis. ROIs for the other samples were chosen to be in similar positions with respect to spleen boundaries. c. Representation of the four angular pixel directions used in grey level co-occurrence matrix (GLCM) calculations. For each pixel displacement, d, GLCMs were calculated in each angular direction and averaged to give one GLCM per displacement distance. d. Demonstration of the relative positions of three reference pixels used in 3-D GLCM calculations for the case of d = 2 and θ = 45°. For 2-D GLCM calculations only pixels i and j were compared. 3-D GLCM analysis incorporates depth information by including a third reference pixel, k, in the z direction. Pixel position changes Δx, Δy and Δz can be calculated from Eq. (1).

Mentions: Quantitative analysis of internal structures was performed by comparing various textural statistics between samples. Due to the irregular size and shapes of the spleens, regions-of-interest (ROIs) of size 200 × 200 × 30 pixels in similar positions were analysed for each sample, as shown in Fig. 2.


Detecting microvascular changes in the mouse spleen using optical computed tomography.

McErlean CM, Boult JK, Collins DJ, Leach MO, Robinson SP, Doran SJ - Microvasc. Res. (2015)

a. and b. Orthogonal cross-section slices of a reconstructed ZD6126-treated spleen image volume from Dataset 2 with FOV (5.3 mm)3. The yellow boxes indicate the position of the region-of-interest (ROI) (size 200 × 200 × 30 pixels) chosen for textural feature analysis. ROIs for the other samples were chosen to be in similar positions with respect to spleen boundaries. c. Representation of the four angular pixel directions used in grey level co-occurrence matrix (GLCM) calculations. For each pixel displacement, d, GLCMs were calculated in each angular direction and averaged to give one GLCM per displacement distance. d. Demonstration of the relative positions of three reference pixels used in 3-D GLCM calculations for the case of d = 2 and θ = 45°. For 2-D GLCM calculations only pixels i and j were compared. 3-D GLCM analysis incorporates depth information by including a third reference pixel, k, in the z direction. Pixel position changes Δx, Δy and Δz can be calculated from Eq. (1).
© Copyright Policy - CC BY
Related In: Results  -  Collection

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f0015: a. and b. Orthogonal cross-section slices of a reconstructed ZD6126-treated spleen image volume from Dataset 2 with FOV (5.3 mm)3. The yellow boxes indicate the position of the region-of-interest (ROI) (size 200 × 200 × 30 pixels) chosen for textural feature analysis. ROIs for the other samples were chosen to be in similar positions with respect to spleen boundaries. c. Representation of the four angular pixel directions used in grey level co-occurrence matrix (GLCM) calculations. For each pixel displacement, d, GLCMs were calculated in each angular direction and averaged to give one GLCM per displacement distance. d. Demonstration of the relative positions of three reference pixels used in 3-D GLCM calculations for the case of d = 2 and θ = 45°. For 2-D GLCM calculations only pixels i and j were compared. 3-D GLCM analysis incorporates depth information by including a third reference pixel, k, in the z direction. Pixel position changes Δx, Δy and Δz can be calculated from Eq. (1).
Mentions: Quantitative analysis of internal structures was performed by comparing various textural statistics between samples. Due to the irregular size and shapes of the spleens, regions-of-interest (ROIs) of size 200 × 200 × 30 pixels in similar positions were analysed for each sample, as shown in Fig. 2.

Bottom Line: A significant difference in total splenic volume was found between vehicle and ZD6126-treated cohorts, with mean volumes of 61±3mm(3) and 44±3mm(3) respectively (both n=3, p=0.05).Textural statistics for each sample were calculated using grey-level co-occurrence matrices (GLCMs).Standard 2-D GLCM analysis was found to be slice-dependent while 3-D GLCM contrast and homogeneity analysis resulted in separation of the vehicle and ZD6126-treated cohorts over a range of length scales.

View Article: PubMed Central - PubMed

Affiliation: Cancer Research UK Cancer Imaging Centre, The Institute of Cancer Research, Sutton SM2 5NG, UK. Electronic address: cmcerlean@icr.ac.uk.

No MeSH data available.


Related in: MedlinePlus