Granted Patent B2

US 12,646,171 · App. 18/676,460 · Granted Jun 2, 2026

Inventors: Brent Stephen Robinson (Mount Pleasant, NZ); Bruce Leslie Keith Davey (Christchurch, NZ); Philip John Barclay (Westmorland, NZ); Rachel Anne Johnston (Avonhead, NZ)

Assignee: Aranz Medical Limited

G06T7/0012G06V10/25G06V10/469G06T2207/20104G06T2207/30088

Abstract

Claims (41)

1 . A computer-implemented method of assessing a surface feature on a patient's skin surface, comprising:

capturing, at an image capture device, one or more data sets of a patient's skin surface including the skin surface feature;

determining outline data of the skin surface feature based on at least one of the one or more data sets, wherein the determined outline data includes sub-region outline data for one or more sub-regions of the skin surface feature;

determining one or more confidence attributes associated with the determined outline data, wherein the one or more confidence attributes include one or more sub-region confidence attributes;

storing in a non-volatile memory—

a representation of the skin surface and/or the skin surface feature;

at least part of the determined outline data including at least part of the sub-region outline data; and

one or more visual representations of the one or more confidence attributes, wherein the one or more visual representations include at least some of the sub-region confidence attributes; and

displaying to a user via a graphical user interface—

one or more representations of the skin surface and/or the skin surface feature;

at least part of the determined outline data including at least part of the sub-region outline data; and

one or more visual representations of the one or more confidence attributes, including at least some of the sub-region confidence attributes.

2 . The method of claim 1 wherein the one or more sub-region confidence attributes include one or more of:

one or more confidence attributes for the sub-region outline data;

a plurality of sub-region segment confidence attributes, each associated with a segment of the sub-region outline data; and/or

a plurality of sub-region point confidence attributes, each associated with a point in the sub-region outline data.

3 . The method of claim 1 , further comprising rejecting the sub-region outline data or part of the sub-region outline data if one or more of the sub-region confidence attributes are unacceptable.

4 . The method of claim 1 wherein the determined outline data includes a determined surface feature outline and the at least one of the one or more confidence attributes include one or more of:

a confidence attribute for the determined surface feature outline as a whole;

a plurality of segment confidence attributes, each associated with a segment of the determined surface feature outline; and/or

a plurality of point confidence attributes, each associated with a point on the determined surface feature outline.

5 . The method of claim 1 wherein determining the one or more confidence attributes is based at least in part on distances between points in the determined outline data.

6 . The method of claim 1 , further comprising processing the determined outline data, wherein determining the one or more confidence attributes is based at least in part on distances between points in the determined or processed outline data and points in the one or more data sets.

7 . The method of claim 1 , further comprising soliciting user input of data having confidence attributes that are unacceptable.

8 . The method of claim 1 , wherein displaying to the user via the graphical user interface the one or more visual representations of the one or more confidence attributes includes displaying to the user, via the graphical user interface, one or more of: a numerical confidence indicator, a confidence symbol indicator, a colored confidence indicator, a patterned confidence indicator, and/or a confidence scale indicator.

9 . A computer-implemented method of assessing a surface feature on a patient's skin surface, including:

capturing, at an image capture device, one or more data sets of a patient's skin surface including the skin surface feature;

determining outline data of the skin surface feature based on at least one of the one or more data sets, wherein the determined outline data includes sub-region outline data for one or more sub-regions of the skin surface feature;

determining one or more tissue types associated with each of the sub-regions;

determining one or more confidence attributes associated with the determined outline data, wherein the one or more confidence attributes include one or more sub-region confidence attributes;

determining a tissue confidence attribute associated with the determined tissue type for each of the sub-regions;

storing in a non-volatile memory—

a representation of the skin surface and/or the skin surface feature;

at least part of the determined outline data including at least part of the sub-region outline data; and

one or more visual representations of the one or more confidence attributes, wherein the one or more visual representations include at least some of the sub-region confidence attributes; and

displaying to a user via a graphical user interface—

one or more representations of the skin surface and/or the skin surface feature;

at least part of the determined outline data including at least part of the sub-region outline data; and

one or more visual representations of the one or more confidence attributes, including at least some of the sub-region confidence attributes.

10 . The method of claim 9 , further comprising soliciting user input of data having confidence attributes that are unacceptable.

11 . The method of claim 9 wherein displaying to the user via the graphical user interface the one or more visual representations of the one or more confidence attributes includes displaying, to the user via the graphical user interface, one or more of: a numerical confidence indicator, a confidence symbol indicator, a colored confidence indicator, a patterned confidence indicator, and/or a confidence scale indicator.

Assignments (1)

Continuity (3)

References Cited (400)