Patent ID: 11922633
Assignee: CANON U.S.A., INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G  A | IPC G

Claim 9:
10. The method of claim 7, wherein one or more of the following:
(i) the detecting of the border or borders of the A-line cross-section(s) and/or performing segmentation procedure(s) of the 3D A-line cross-section(s) step is performed automatically;
(ii) the detecting of the border or borders of the A-line cross-section(s) and/or performing segmentation procedure(s) of the 3D A-line cross-section(s) step is more precise since less variance is in the 3D A-line cross-section or cross-sections than a 2D OCT cross-section;
(iii) the detecting of the border or borders step may include one or more of the following:
(a) applying bilateral filtering and deleting the catheter or probe from an image or images;
(b) applying Otsu's automatic thresholding;
(c) applying a filtering technique and/or applying automatic thresholding;
(d) smoothing the segmented images by deleting objects or small objects which correspond to image artifacts;
(e) scanning the image from one portion of the image to another portion of the image, storing the first non-zero pixel and, in a case where the y coordinate of the first (x1,y1) and last (xend,yend) detected point differ from the first (c1) and last (cend) column of the image, respectively, then adding as first point: (x1,c1) and as last point: (x1,cend); and/or
(f) connecting the detected non-zero pixel using a linear interpolation function;

(iv) the bilateral filter for an image H, and a window mask W is defined as:, I
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  ,, having a normalization factor Wp:, Wp=Σxi∈Wfr(∥I(xi)−I(x)∥)gs(∥xi−x∥), where x are the coordinates of a central pixel of the mask and the parameters fr and gs are the Gaussian kernel for smoothing differences in intensities and the spatial Gaussian kernel for smoothing differences in coordinates;
(v) to automatically threshold the 3D A-line cross-section(s) images, a threshold Throtsu for the image I′ is calculated using the Otsu's method, and the pixels of the image I′ that are smaller than Throtsu are set to a zero value such that a result is a binary image with the arterial wall represented by the non-zero objects;
(vi) the 3D A-line cross-section(s) images are automatically thresholded; and/or
(vii) the method further comprises detecting the objects that are smaller than 3% of the whole image to ensure that only the objects that correspond to the wall area are used to detect the border or borders.