11 Segmentation and Visualization of Drusen …
323
(2) Flattening of sub-RPE region: An image is composed by taking the recorded
intensity values beneath the segmented BM boundary up to a maximum depth
where GA can be detected, constituting a flattened sub-RPE image. This maximum depth is set up as an independent parameter in this work (depth of sub-RPE,
as explained in the later parameter evaluation). The flattened sub-RPE region is
shown in Fig. 11.26a.
(3) Finding local maximum intensity points. For each column in the flattened
sub-RPE region (A-scan location), the points with local maximum intensity
value (namely the intensity value of the point is larger than those of its two
connected points) are found, as marked with the blue circle in Fig. 11.28.
(4) Locating maximum intensity points at higher depths. The maximum intensity points whose value follows a constantly decreasing function with depth (x
axis) are selected, as marked with the magenta stars in Fig. 11.28. The purpose
of this step is to ensure a constantly descendent intensity profile beneath RPE.
(5) Calculating the area below the surface constructed with the maximum
intensity points at higher depths. We interpolate the intensity profile in the
axial locations between the selected maximum intensity points at higher depths
using linear interpolation (magenta lines in Fig. 11.28), and calculate the area of
the polygon formed by this interpolation and a baseline of zero intensity (area
below the magenta lines marked in Fig. 11.28).
(6) Taking the calculated area above as the primary GA projection value at
each projection location.
(7) Using a median filter to smooth the generated GA projection image: To
alleviate the noise influence and make the final GA projection image smoother,
a simple median filter with a 3 × 3 neighborhood was used.
Figure 11.29a shows the GA projection image with the proposed RSAP technique, and Fig. 11.29b shows a detail comparison of three GA projection techniques
in regions of interest corresponding to the red dashed rectangles in Fig. 11.30a. Compared with the SVP and Sub-RPE Slab projection images (Fig. 11.25a and b), the
RSAP projection image displays a higher contrast and also overcomes the influence
of the choroidal vasculature on GA visualization, as shown in Fig. 11.29b.
11.3.3.2 Results
The proposed RSAP technique was tested and compared with the SVP and SubRPE Slab techniques qualitatively and quantitatively. The influence of the parameter
controlling the maximum considered depth for the sub-RPE region, mentioned earlier, was first evaluated and later fixed for all 99 test images. Figure 11.30 shows
the GA separability for different depths of sub-RPE regions in one SD-OCT image,
where the depth was varied from 100 to 300 pixels (approximately 0.2–0.6 mm in
the collected images) with an interval of 10 pixels. Figure 11.30 demonstrates that
the GA separability increases when the depth increases from 100 to 240 pixels, and
then remains stable with further depth increases. Figure 11.31 shows the relation-
323
(2) Flattening of sub-RPE region: An image is composed by taking the recorded
intensity values beneath the segmented BM boundary up to a maximum depth
where GA can be detected, constituting a flattened sub-RPE image. This maximum depth is set up as an independent parameter in this work (depth of sub-RPE,
as explained in the later parameter evaluation). The flattened sub-RPE region is
shown in Fig. 11.26a.
(3) Finding local maximum intensity points. For each column in the flattened
sub-RPE region (A-scan location), the points with local maximum intensity
value (namely the intensity value of the point is larger than those of its two
connected points) are found, as marked with the blue circle in Fig. 11.28.
(4) Locating maximum intensity points at higher depths. The maximum intensity points whose value follows a constantly decreasing function with depth (x
axis) are selected, as marked with the magenta stars in Fig. 11.28. The purpose
of this step is to ensure a constantly descendent intensity profile beneath RPE.
(5) Calculating the area below the surface constructed with the maximum
intensity points at higher depths. We interpolate the intensity profile in the
axial locations between the selected maximum intensity points at higher depths
using linear interpolation (magenta lines in Fig. 11.28), and calculate the area of
the polygon formed by this interpolation and a baseline of zero intensity (area
below the magenta lines marked in Fig. 11.28).
(6) Taking the calculated area above as the primary GA projection value at
each projection location.
(7) Using a median filter to smooth the generated GA projection image: To
alleviate the noise influence and make the final GA projection image smoother,
a simple median filter with a 3 × 3 neighborhood was used.
Figure 11.29a shows the GA projection image with the proposed RSAP technique, and Fig. 11.29b shows a detail comparison of three GA projection techniques
in regions of interest corresponding to the red dashed rectangles in Fig. 11.30a. Compared with the SVP and Sub-RPE Slab projection images (Fig. 11.25a and b), the
RSAP projection image displays a higher contrast and also overcomes the influence
of the choroidal vasculature on GA visualization, as shown in Fig. 11.29b.
11.3.3.2 Results
The proposed RSAP technique was tested and compared with the SVP and SubRPE Slab techniques qualitatively and quantitatively. The influence of the parameter
controlling the maximum considered depth for the sub-RPE region, mentioned earlier, was first evaluated and later fixed for all 99 test images. Figure 11.30 shows
the GA separability for different depths of sub-RPE regions in one SD-OCT image,
where the depth was varied from 100 to 300 pixels (approximately 0.2–0.6 mm in
the collected images) with an interval of 10 pixels. Figure 11.30 demonstrates that
the GA separability increases when the depth increases from 100 to 240 pixels, and
then remains stable with further depth increases. Figure 11.31 shows the relation-