IP Library Granted Patent US 12,475,586
Granted Patent B2
US 12,475,586 · App. 18/601,986 · Granted Nov 18, 2025

Systems and methods for generating three-dimensional measurements using endoscopic video data

Inventors: Cole Kincaid Hunter (Helena, MT); Brian Fouts (Morgan Hill, CA); Sanskruti Maske (Gondia, IN)
Assignee: Stryker Corporation
G06T7/60A61B1/000094A61B34/10G01S17/894G06T7/11G06T7/593G06T17/00A61B2034/105G06T2200/24G06T2207/10012G06T2207/10016G06T2207/10068G06T2207/20081
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,475,586
App. No.
18/601,986
Granted
Nov 18, 2025
Kind
B2
Abstract

Presented herein are systems and methods for performing three-dimensional measurements of a surgical space using two-dimensional endoscopic images. According to an aspect, video data taken from an endoscopic imaging device can be used to generate a three-dimensional model of the surgical space represented by the video data. In one or more examples, two-dimensional images from the video data can be used to generate a three-dimensional model of the surgical space. In one or more examples, the one or more two-dimensional images of the surgical space can include a fiducial marker as part of the image. Using both the depth information and a size reference provided by the fiducial marker, the systems and methods herein can generate a three-dimensional model of the surgical space. The generated three-dimensional model can then be used to perform a variety of three-dimensional measurements in a surgical cavity in an accurate and efficient manner.

Claims (38)

1 . A method for measuring distances using endoscopic images, the method comprising:

receiving, at one or more processors, video data from an endoscopic imaging device configured to image an internal area of a patient, wherein the video data comprises one or more two-dimensional images that capture one or more fiducials;

identifying, by the one or more processors, a first point of the internal area of the patient in the one or more two-dimensional images;

identifying, by the one or more processors, a second point of the internal area of the patient in the one or more two-dimensional images; and

determining, by the one or more processors and based on the one or more fiducials, a measurement between the first point and the second point that accounts for curvature of the internal area of the patient.

2 . The method of claim 1 , wherein determining the measurement comprises using the one or more fiducials for scale.

3 . The method of claim 1 , wherein determining the measurement comprises determining depth information based on the one or more two-dimensional images.

4 . The method of claim 3 , wherein the depth information is determined from motion between multiple images of the one or more images.

5 . The method of claim 3 , wherein the depth information is determined using a machine learning model on a single image of the one or more images.

6 . The method of claim 1 , wherein the measurement is determined based on a three-dimensional model of the internal area of the patient.

7 . The method of claim 6 , wherein determining the measurement comprises generating the three-dimensional model based on the one or more two-dimensional images.

8 . The method of claim 1 , wherein the one or more fiducials comprises an object of a predetermined size.

9 . The method of claim 1 , wherein the one or more fiducials comprises a fiducial marker disposed on a surface of a surgical instrument.

10 . The method of claim 1 , wherein identifying the first point of the internal area of the patient in the one or more two-dimensional images comprises identifying the first point based on a received first user input, and wherein identifying the second point of the internal area of the patient in the one or more two-dimensional images comprises identifying the second point based on a received second user input.

11 . A system for measuring distances using endoscopic images, the system comprising:

a memory; and

one or more processors,

wherein the memory stores one or more programs that when executed by the one or more processors, cause the one or more processors to:

receive video data from an endoscopic imaging device configured to image an internal area of a patient, wherein the video data comprises one or more two-dimensional images that capture one or more fiducials;

identify a first point of the internal area of the patient in the one or more two-dimensional images;

identify a second point of the internal area of the patient in the one or more two-dimensional images; and

determine, based on the one or more fiducials, a measurement between the first point and the second point that accounts for curvature of the internal area of the patient.

12 . The system of claim 11 , wherein determining the measurement comprises using the one or more fiducials for scale.

13 . The system of claim 11 , wherein determining the measurement comprises determining depth information based on the one or more two-dimensional images.

14 . The system of claim 13 , wherein the depth information is determined from motion between multiple images of the one or more images.

15 . The system of claim 13 , wherein the depth information is determined using a machine learning model on a single image of the one or more images.

16 . The system of claim 11 , wherein the measurement is determined based on a three-dimensional model of the internal area of the patient.

17 . The system of claim 16 , wherein determining the measurement comprises generating the three-dimensional model based on the one or more two-dimensional images.

18 . The system of claim 11 , wherein the one or more fiducials comprises an object of a predetermined size.

19 . The system of claim 11 , wherein the one or more fiducials comprises a fiducial marker disposed on a surface of a surgical instrument.

20 . The system of claim 11 , wherein identifying the first point of the internal area of the patient in the one or more two-dimensional images comprises identifying the first point based on a received first user input, and wherein identifying the second point of the internal area of the patient in the one or more two-dimensional images comprises identifying the second point based on a received second user input.

21 . A non-transitory computer readable storage medium storing one or more programs for execution by one or more processors of a computing system, the one or more programs including instructions that, when executed by the computing system, cause the computing system to:

receive video data from an endoscopic imaging device configured to image an internal area of a patient, wherein the video data comprises one or more two-dimensional images that capture one or more fiducials;

identify a first point of the internal area of the patient in the one or more two-dimensional images;

identify a second point of the internal area of the patient in the one or more two-dimensional images; and

determine, based on the one or more fiducials, a measurement between the first point and the second point that accounts for curvature of the internal area of the patient.

22 . The non-transitory computer readable storage medium of claim 21 , wherein determining the measurement comprises using the one or more fiducials for scale.

23 . The non-transitory computer readable storage medium of claim 21 , wherein identifying the first point of the internal area of the patient in the one or more two-dimensional images comprises identifying the first point based on a received first user input, and wherein identifying the second point of the internal area of the patient in the one or more two-dimensional images comprises identifying the second point based on a received second user input.

Assignments (1)
CHANGE OF ADDRESS Recorded Dec 18, 2024
From: STRYKER CORPORATION
To: STRYKER CORPORATION
Reel/Frame 069737/0184 →