ENDOSCOPY SYSTEM WITH MOTION SENSORS

• US 20110032347A1
• Filed: 04/15/2009
• Published: 02/10/2011
• Est. Priority Date: 04/15/2008
• Status: Abandoned Application

• Current Assignee: The Provost Fellows and Scholars of the College of the Holy and Undivided Trinity of Queen Elizabeth, near Dublin
• Original Assignee: The Provost Fellows and Scholars of the College of the Holy and Undivided Trinity of Queen Elizabeth, near Dublin
• Inventors: Vilarino, Fernando, Lacey, Gerard
• Application Number:
  US12/736,536
• Publication Number:
  US 20110032347A1
• Time in Patent Office: Days
• US Class Current: 348/68
• CPC Class Codes: A61B 1/0005 combining images e.g. side-by-side, superimposed or tiled
• CPC Class Codes: A61B 1/00154 using guiding arrangements for insertion
• CPC Class Codes: A61B 1/31 for the rectum, e.g. proctoscopes, sigmoidoscopes , colonoscopes
• CPC Class Codes: A61B 5/065 Determining position of the probe employing exclusively positioning means located on or in the probe, e.g. using position sensors arranged on the probe
• CPC Class Codes: G06T 2200/24 involving graphical user interfaces [GUIs]
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/10068 Endoscopic image
• CPC Class Codes: G06T 2207/30032 Colon polyp
• CPC Class Codes: G06T 7/0012 Biomedical image inspection

Abstract

An endoscopy system (1) comprises an endoscope (2) with a camera (3) at its tip. The endoscope extends through an endoscope guide (4) for guiding movement of the endoscope and for measurement of its movement as it enters the body. The guide (4) comprises a generally conical body (5) having a through passage (105) through which the endoscope (2) extends. A motion sensor comprises an optical transmitter (7) and a detector (8) mounted alongside the passage (105) to measure the insertion-withdrawal linear motion and also rotation of the endoscope by the endoscopist'"'"'s hand. The system (1) also comprises a flexure controller (10) having wheels operated by the endoscopist. The camera (3), the motion sensor (7/8), and the flexure controller (10) are all connected to a processor (11) which feeds a display.

Claims

1. An endoscopy system comprising:

an endoscope having a camera;

an image processor for receiving endoscopic images from the camera and for processing the images;

a motion sensor adapted to measure linear motion of the endoscope through a patient orifice; and

a processor adapted to use results of image processing and motion measurements to generate an output indicative of a disease and of quality of the endoscopy procedure.

wherein the processor is adapted to;

generate outputs arising from testing current measured motion and image processing results against a plurality of correlation requirements, perform a quality control for endoscopy because of correlation of motion sensor measurement data and image processing data, and generating an output including an objective assessment of the endoscopist handling skills and an assessment of quality of the endoscopy based on how well the lumen was visualized, and to generate an alert if it determines that the camera has moved too quickly to adequately view a part of the lumen.

2. The system as claimed in claim 1, wherein the motion sensor comprises means for measuring extent of rotation of the endoscope, and the processor is adapted to use said motion data.

3. The system as claimed in either of claim 1, wherein the motion sensor comprises a light emitter and a light detector on a fixed body through which the endoscope passes.

4. The system as claimed in claim 1, wherein the system comprises an endoscope tip flexure controller and the processor is adapted to receive and process endoscope tip flexure data and for correlating it with endoscope motion data and image processing results.

5. The system as claimed in claim 1, wherein the processor is adapted to perform visualisation quality assessment.

6. The system as claimed in claim 1, wherein the processor is adapted to perform visualisation quality assessment by automatically determining if visual display image rate is lower than a threshold required to adequately view a part of the lumen.

7. The system as claimed in claim 1, wherein the processor is adapted to perform visualisation quality assessment by automatically determining if visual display image rate is lower than a threshold required to adequately view a part of the lumen, and wherein the processor is adapted to vary said threshold according to conditions.

8. The system as claimed in claim 1, wherein the processor is adapted to perform visualisation quality assessment by automatically determining if visual display image rate is lower than a threshold required to adequately view a part of the lumen, and wherein the processor is adapted to vary said threshold according to conditions;

and wherein a condition is detection of salient features during image processing, said salient features being potentially indicative of a disease and the threshold is set at a level providing sufficient time to view the images from which the salient features were derived.

9. The system as claimed in claim 1, wherein the processor is adapted to perform visualisation quality assessment by automatically determining if visual display image rate is lower than a threshold required to adequately view a part of the lumen;

and wherein the processor is adapted to determine from endoscope tip three dimensional and linear motion if the lumen has been adequately imaged.

10. The system as claimed in claim 1, wherein the processor is adapted to perform visualisation quality assessment;

and wherein the processor is adapted to execute a classifier to quantify visualisation quality.

11. The system as claimed in claim 1, wherein the processor is adapted to perform visualisation quality assessment;

and wherein the processor is adapted to execute a classifier to quantify visualisation quality; and

wherein the classifier is a support vector machine.

12. The system as claimed in claim 1, wherein the processor is adapted to perform visualisation quality assessment;

and wherein the processor is adapted to process eye tracking data and to associate this with motion of the endoscope to measure the ability of a clinician to perceive disease.

13. The system as claimed in claim 1, wherein the processor is adapted to perform visualisation quality assessment;

and wherein the processor is adapted to process eye tracking data and to associate this with motion of the endoscope to measure the ability of a clinician to perceive disease; and

wherein the eye-tracking data is stored as calibration data.

14. The system as claimed in claim 1, wherein the processor is adapted to generate an internal map of a patient'"'"'s intestine using image processing results and motion measurements referenced against stored models.

15. The system as claimed in claim 1, wherein the processor is adapted to generate an internal map of a patient'"'"'s intestine using image processing results and motion measurements referenced against stored models;

and wherein the processor is adapted to store images from which the map is derived, for traceability.

17. The system as claimed in claim 1, wherein a requirement is that the endoscope should not be pushed further through the patient'"'"'s orifice when the image processing indicates that the endoscope is against a lumen wall.

18. The system as claimed in claim 1, wherein a requirement is that a required set of endoscope linear and rotational movements are performed to flick the endoscope out of a loop, the loop being indicated by the image processing results.

19. The system as claimed in claim 1, wherein the processor is adapted to generate a disease risk indication according to the image processing and to include disease location information with reference to an intestine map.

20. The system as claimed in claim 1, wherein the processor is adapted to apply a weight to each of a plurality of image-related factors to generate the output.

21. The system as claimed in claim 1, wherein the processor is adapted to generate a disease risk indication according to the image processing and to include disease location information with reference to an intestine map;

and wherein the factors include focus, illumination, features, and image motion.

22. The system as claimed in claim 1, wherein the processor is adapted to generate a display indicating meta data of high risk regions of the lumen.

23. The system as claimed in claim 1, wherein the processor is adapted to increase frame rate of a display where the disease risk is low.

24. The system as claimed in claim 1, wherein the system comprises a classifier such as a support vector machine to classify the risks of missing a lesion.

25. The system as claimed in claim 1, wherein the processor is adapted to generate an indication of repetition of a procedure

26. The system as claimed in claim 1, wherein the processor is adapted to un-wrap a three-dimensional map into a two-dimensional map for display.

27. The system as claimed in claim 1, wherein the processor is adapted to un-wrap a three-dimensional map into a two-dimensional map for display;

and wherein the processor is adapted to represent in two dimensions areas of extreme shape change with contour lines in a manner similar to those used on maps.

28. The system as claimed in claim 1, wherein the processor is adapted to un-wrap a three-dimensional map into a two-dimensional map for display;

and wherein the processor is adapted to represent in two dimensions areas of extreme shape change with contour lines in a manner similar to those used on maps; and

wherein the processor is adapted to extract a three-dimensional structure of a lumen is using sparse keypoint tracking based on visual simultaneous localization and mapping, and to detect key points in two-dimensional images.

16. (canceled)