IP Library › Granted Patent US 11,715,202
Granted Patent B2
US 11,715,202 · App. 17/469,101 · Granted Aug 1, 2023

Analyzing apparatus and analyzing method

Inventors: Yasunori Honjo (Kawasaki, JP); Yu Igarashi (Kawasaki, JP); Masaki Watanabe (Kawasaki, JP)
Assignee: CANON MEDICAL SYSTEMS CORPORATION
G06T7/0012A61B5/7271A61B8/485A61B8/5223G06T7/11G06T7/187G06T11/60G06V10/50A61B5/7475G06T2207/10132G06T2207/20021G06T2207/20081G06T2207/30004G06T2207/30024G06T2210/41
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Quick Facts
Patent No.
US 11,715,202
App. No.
17/469,101
Granted
Aug 1, 2023
Kind
B2
Abstract

An analyzing apparatus according to an embodiment includes processing circuitry. The processing circuitry is configured to calculate a tissue characteristic parameter value with respect to each of a plurality of positions within a region of interest, by analyzing a result of a scan performed on a patient. The processing circuitry is configured to determine a measurement region in the region of interest by performing an analysis while using the tissue characteristic parameter values. The processing circuitry is configured to calculate a statistic value of the tissue characteristic parameter values in the measurement region.

Claims (34)

1. An analyzing apparatus comprising processing circuitry configured:

to calculate a tissue characteristic parameter value with respect to each of a plurality of positions within a region of interest, by analyzing a result of a scan performed on a patient;

to obtain

an index value indicating a degree of stability of the calculated tissue characteristic parameter value for each of a plurality of sub-regions in the region of interest by using the tissue characteristic parameter value as an input to a trained model with respect to each of the sub-regions; and

to determine a measurement region

in the region of interest based on the obtained index value.

2. The analyzing apparatus according to claim 1 , wherein the processing circuitry determines the measurement region by comparing the index value of each of the plurality of sub-regions with a threshold value.

3. The analyzing apparatus according to claim 2 , wherein the processing circuitry is further configured to change the threshold value.

4. The analyzing apparatus according to claim 2 , wherein the processing circuitry changes the threshold value in accordance with a site of the patient subject to a measuring process.

5. The analyzing apparatus according to claim 1 , wherein the processing circuitry is further configured to display the measurement region over an image based on the tissue characteristic parameter value.

6. The analyzing apparatus according to claim 1 , wherein the processing circuitry is further configured to calculate a statistic value of the tissue characteristic parameter value in the measurement region.

7. The analyzing apparatus according to claim 6 , wherein, as the statistic value, the processing circuitry calculates one selected from among an average value, a median, a variance value, a standard deviation, and a residual sum of squares, with respect to the tissue characteristic parameter values.

8. The analyzing apparatus according to claim 1 , wherein the processing circuitry obtains the index value of each of the plurality of sub-regions by using distribution information of the tissue characteristic parameter value with respect to each sub-region as an input to the trained model.

9. The analyzing apparatus according to claim 8 , wherein the processing circuitry obtains the index value of each sub-region by inputting to the trained model the tissue characteristic parameter value of a pixel in each sub-region and the number of pixels corresponding to the tissue characteristic parameter value as the distribution information.

10. The analyzing apparatus according to claim 9 , wherein the processing circuitry obtains the index value of each of the plurality of sub-regions by using a histogram for each sub-region indicating a correspondence relationship between the tissue characteristic parameter value and the number of pixels as an input to the trained model.

11. The analyzing apparatus according to claim 1 , wherein the processing circuitry obtains, as the index value, a stability score indicating a degree of stability of the tissue characteristic parameter value in each sub-region.

12. The analyzing apparatus according to claim 1 , wherein the trained model is trained to learn a correspondence relationship between the tissue characteristic parameter value in various sub-regions, the number of pixels corresponding to the tissue characteristic parameter value in the various sub-regions, and a stability score indicating a degree of stability of the tissue characteristic parameter value in the various sub-regions.

13. The analyzing apparatus according to claim 1 , wherein the processing circuitry is further configured to display the sub-region over an image based on the tissue characteristic parameter value.

14. The analyzing apparatus according to claim 1 , wherein the processing circuitry is further configured to change a size of the sub-region.

15. The analyzing apparatus according to claim 1 , wherein the processing circuitry calculates, as the tissue characteristic parameter value, a parameter based on a shear wave.

16. The analyzing apparatus according to claim 1 , wherein, as the tissue characteristic parameter value, the processing circuitry calculates, with respect to positions where the scan was performed, one selected from among shear velocity values, arrival times, elasticity modulus values, velocity values, displacement values, strain values, attenuation values, and brightness local variance values.

17. The analyzing apparatus according to claim 1 , wherein the trained model outputs the index value indicating a degree of stability of the tissue characteristic parameter value for each of the plurality of sub-regions in response to input of the tissue characteristic parameter value for each of the plurality of sub-regions.

18. An analyzing apparatus comprising processing circuitry configured:

to calculate a tissue characteristic parameter value with respect to each of a plurality of positions within a region of interest, by analyzing a result of a scan performed on a patient;

to obtain

an index value indicating a degree of stability of the calculated tissue characteristic parameter value for each of a plurality of sub-regions in the region of interest by using the tissue characteristic parameter value as an input to a trained model with respect to each of the sub-regions; and

to determine a measurement candidate region in the region of interest based on the obtained index values.

19. The analyzing apparatus according to claim 18 , wherein the processing circuitry determines the measurement candidate region by comparing the index value of each of the plurality of sub-regions with a threshold value.

20. The analyzing apparatus according to claim 19 , wherein the processing circuitry determines at least one measurement candidate region from within a region combining together two or more of the sub-regions that are each determined, as a result of the comparison, to exhibit a high level as the degree of stability.

21. The analyzing apparatus according to claim 20 , wherein the processing circuitry determines one or more measurement candidate regions of which a quantity is determined in advance.

22. The analyzing apparatus according to claim 20 , wherein, as the measurement candidate region, the processing circuitry determines a circular region having a largest diameter.

23. The analyzing apparatus according to claim 18 , wherein the processing circuitry is further configured to display the measurement candidate region over an image of the patient in the region of interest.

24. The analyzing apparatus according to claim 18 , wherein the processing circuitry is further configured to determine a measurement region in the measurement candidate region.

25. The analyzing apparatus according to claim 18 , wherein the processing circuitry determines the measurement candidate region having a shape and a size that are set in advance.

Priority Claims (2)
JP 2016-144697 · Jul 22, 2016 · national
JP 2017-140280 · Jul 19, 2017 · national
Continuity (2)
Continuation 15656599 · Jul 21, 2017
Related Publication 20210407084A1 · Dec 30, 2021