Method and system for detecting colorimetric abnormalities in vivo
A system and method for detection of colorimetric abnormalities within a body lumen includes an image receiver for receiving images from within the body lumen. Also included are a transmitter for transmitting the images to a receiver, and a processor for generating a probability indication of presence of colorimetric abnormalities on comparison of color content of the images and at least one reference value.
1. A method for processing in-vivo information, the method comprising:
receiving, at a data processor, data generated by a swallowable in-vivo device traversing a gastrointestinal tract, the data comprising a set of in-vivo images of the gastrointestinal tract;
the data processor comparing values of an image from the received set of images to a reference value of blood;
the data processor calculating an adaptive reference value of healthy tissue for the image, based on averaging parameters of images of healthy tissue, the images previous to the image in the received set of images;
the data processor comparing values of the image to the adaptive reference value of healthy tissue; and
based on the comparisons, the data processor generating a probability indication of a presence of blood in the image.
2. The method of claim 1 , further comprising displaying, based on the probability indication, a color video showing a presence of bleeding.
3. The method of claim 1 , further comprising displaying a position in the gastrointestinal tract where the image was taken.
4. The method of claim 1 , wherein the values of the image comprise colorimetric parameters.
5. The method of claim 1 , wherein the values of the image comprise color components.
6. The method of claim 1 , wherein the presence of blood in the image is a presence of bleeding.
7. The method of claim 1 , wherein comparing values of the image from the received set of images to the reference value of blood comprises calculating a Euclidian distance between the values of the image and the reference value of blood.
8. The method of claim 1 , wherein comparing values of the image to the adaptive reference value of healthy tissue comprises calculating a Euclidian distance between the values of the image and the adaptive reference value of healthy tissue.
9. A system for processing in-vivo information, the system comprising:
a data processor configured to:
receive data generated by a swallowable in-vivo device traversing a gastrointestinal tract, the data comprising a set of in-vivo images of the gastrointestinal tract;
compare values of an image from the received set of images to a reference value of blood;
calculate an adaptive reference value of healthy tissue for the image, based on averaging parameters of images of healthy tissue, the images previous to the image in the received set of images;
compare values of the image to the adaptive reference value of healthy tissue; and
based on the comparisons, generate a probability indication of a presence of blood in the image.
10. The system of claim 9 , further comprising the swallowable in-vivo device.
11. The system of claim 9 , further comprising a receiver for receiving signals from an in-vivo device.
12. The system of claim 9 , further comprising a monitor to display, based on the probability indication, a color video showing a presence of bleeding.
13. The system of claim 9 , further comprising a monitor configured to display a position in the gastrointestinal tract where the image was taken.
14. The system of claim 9 , wherein the values of the image comprise colorimetric parameters.
15. The system of claim 9 , wherein the values of the image comprise color components.
16. The system of claim 9 , wherein the presence of blood in the image is a presence of bleeding.
17. The system of claim 9 , wherein comparing values of the image from the received set of images to the reference value of blood comprises calculating a Euclidian distance between the values of the image and the reference value of blood.
18. The system of claim 9 , wherein comparing values of the image to the adaptive reference value of healthy tissue comprises calculating a Euclidian distance between the values of the image and the adaptive reference value of healthy tissue.