System and method for detection of transitions in an image stream of the gastrointestinal tract

Patent metadata

Field	Value
Publication number	US-9324145-B1
Application number	US-201414454975-A
Country	US
Kind code	B1
Filing date	Aug 8, 2014
Priority date	Aug 8, 2013
Publication date	Apr 26, 2016
Grant date	Apr 26, 2016

Abstract

A system and method for detecting a transition in a stream of images of a gastrointestinal (GI) tract may include selecting images from an in-vivo image stream; calculating a segment score for each selected image indicating in which segment of the GI tract the image was captured; applying a smoothing function on the scores; detecting a global step in the smoothed segment score signal indicating a substantial change in a parameter calculated based on segment score signal values of the segment score signal values; detecting a local step indicating a substantial change in a parameter calculated based on segment score signal values of a predetermined interval of the of the segment score signal values; combining the local step and the global step; and determining a point of transition in the stream from one anatomical segment to another, the point of transition correlating to the combined step.

First claim

The invention claimed is:

1. A computer-implemented method for detecting a transition in a stream of in-vivo images of a gastrointestinal (GI) tract, the method comprising:
receiving an in-vivo image stream from an in vivo imaging device;
selecting a subset of images from the image stream for analysis;
calculating a segment score for each selected image, the segment score indicating in which anatomic segment of the GI tract the image was captured;
applying a smoothing function on the segment scores of the selected images to obtain a smoothed segment score signal;
detecting a global step in the smoothed segment score signal, said global step indicating a substantial change in a parameter calculated based on the segment score signal values;
detecting a local step in the smoothed segment score signal, said local step indicating a substantial change in a parameter calculated based on segment score signal values of a predetermined interval of the selected images from the image stream;
combining the local step and the global step to obtain a combined step; and
determining a point of transition in the image stream from one anatomical segment to another, the point of transition correlating to the combined step.

2. The method of claim 1 comprising calculating a feature vector for each selected image, the feature vector based on: a villi score, the villi score corresponding to an amount of villi texture found in a selected image; a content score, the content score corresponding to the probability that the image depicts intestinal contents; and a white score, the white score corresponding to pixels in the image which are substantially white.

3. The method of claim 1 comprising:
detecting a bubble sequence in the image stream, the bubble sequence corresponding to a sequence of images, wherein each image of the sequence contains at least a certain predetermined amount of bubbles; and
determining a corrected point of transition according to the detected bubble sequence.

4. The method of claim 3 comprising:
detecting a low segment score sequence, the low segment score sequence including a sequence of images which received a low segment score value relative to images in their vicinity;
detecting an intersection of the bubble sequence and the low segment score sequence; and
determining the middle of the bubble sequence as a corrected point of transition in the image stream.

5. The method of claim 1 wherein the transition in the image stream is from the small bowel to the colon.

6. The method of claim 1 comprising determining a noisiness level of the segment score signal, the noisiness level correlating to the reliability of the segment score signal for determining a point of transition in the image stream.

7. The method of claim 6 comprising, if the noisiness level of the segment score signal is above a predetermined threshold:
calculating a tissue area score for each selected image to obtain a tissue area score signal, the tissue area score per image indicating an amount of tissue which is captured in an image;
determining a step in the tissue area score signal; and
determining the transition in the image stream according to the detected step in the tissue area score signal.

8. The method of claim 1 comprising refining the detected point of transition of the image stream by selecting a new subset of images from the image stream, the new subset selected from the vicinity of the detected point of transition.

9. A system for detecting a transition in a stream of in-vivo images of a gastrointestinal (GI) tract, the system comprising:
a storage unit to store an in-vivo image stream received from an in vivo imaging device;
a processor to:
select a subset of images from the image stream for analysis;
calculate a segment score for each selected image, the segment score indicating in which anatomic segment of the GI tract the image was captured;
apply a smoothing function to the segment scores of the selected images to obtain a smoothed segment score signal;
detect a global step in the smoothed segment score signal, said global step indicating an abrupt change in a parameter calculated based on the segment score signal values;
detect a local step in the smoothed segment score signal, said local step indicating an abrupt change in a parameter calculated based on segment score signal values of a predetermined interval of the selected images from the image stream;
combine the local step and the global step to obtain a combined step; and
determine a transition in the image stream from one anatomical segment to another, the point of transition correlating to the combined step.

10. The system of claim 9 , wherein the processor is to calculate a feature vector for each selected image, the feature vector based on: a villi score, the villi score corresponding to an amount of villi texture found in a selected image; a content score, the content score corresponding to the probability that the pixel depicts intestinal contents; and a white score, the white score indicating pixels values which are substantially white.

11. The system of claim 9 , wherein the processor is to detect a bubble sequence in the image stream, the bubble sequence corresponding to a sequence of images, wherein each image of the sequence contains at least a certain predetermined amount of bubbles; and to correct the point of transition according to the detected bubble sequence.

12. The system of claim 11 , wherein the processor is to: detect a low segment score sequence, detect an intersection of the bubble sequence and the low segment score sequence; and determine the middle of the bubble sequence as a corrected point of transition in the image stream.

13. The system of claim 9 , wherein the transition in the image stream is from the small bowel to the colon.

14. The system of claim 9 , wherein the processor is to determine a noisiness level of the segment score signal.

15. The system of claim 9 , wherein if the noisiness level of the segment score signal is above a predetermined threshold, the processor is to:
calculate a tissue area score for each selected image to obtain a tissue area score signal, the tissue area score per image indicating an amount of tissue which is captured in an image;
determine a step in the tissue area score signal; and
determine the transition in the image stream according to the detected step in the tissue area score signal.

16. The system of claim 9 , wherein the processor is to refine the detected point of transition of the image stream by selecting a new subset of images from the image stream, the new subset selected from the vicinity of the detected point of transition.

17. The system of claim 9 , wherein the abrupt change in the parameter calculated based on the segment score signal values is a maximal detected change.

18. A method for detecting a transition in a stream of in-vivo images of a gastrointestinal (GI) tract, the method comprising:
selecting images from an in-vivo image stream;
calculating a rating for each selected image, the rating indicating a probability that the image was captured in a predetermined anatomic segment of the GI tract;
applying a smoothing function on the ratings of the selected images to obtain a rating function;
detecting a global increment in the smoothed segment score signal indicating a maximal change in a parameter calculated based on the segment score signal values;
detecting a local increment in the smoothed segment score signal indicating a maximal change in a parameter calculated based on a predeterm

Assignees

• Given Imaging Ltd

Inventors

• Cherevatsky Boris
• Peleg Dori

Classifications

• G06V10/764

  using classification, e.g. of video objects · CPC title

• G06F18/2411

  based on the proximity to a decision surface, e.g. support vector machines · CPC title

• A61B1/000096

  using artificial intelligence · CPC title

• A61B1/000094

  extracting biological structures · CPC title

• A61B5/066

  Superposing sensor position on an image of the patient, e.g. obtained by ultrasound or x-ray imaging · CPC title