System and method for detecting abnormal tissue using vascular features
US-2020359884-A1 · Nov 19, 2020 · US
US12201260B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12201260-B2 |
| Application number | US-202117476604-A |
| Country | US |
| Kind code | B2 |
| Filing date | Sep 16, 2021 |
| Priority date | Mar 18, 2019 |
| Publication date | Jan 21, 2025 |
| Grant date | Jan 21, 2025 |
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A diagnosis support apparatus includes a processor including at least one piece of hardware. The processor identifies, based on physical information including one or more kinds of information capable of estimating a state of a diagnosis target organ of a subject, one abnormal symptom appearing in the diagnosis target organ, performs, as lesion extraction processing for extracting a lesion candidate region from an endoscopic image, different processing specialized for each abnormal symptom that appears in the diagnosis target organ, and performs the lesion extraction processing corresponding to the identified one abnormal symptom.
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What is claimed is: 1. A control apparatus comprising: one or more processors comprising hardware, wherein the one or more processors are configured to: identify, based on physical information inputted, an estimated state of a diagnosis target organ; select a lesion extraction process associated with the estimated state of the diagnosis target organ from a plurality of different lesion extraction processes for extracting a lesion candidate region from an endoscopic image; and perform the lesion extraction process selected to extract the lesion candidate region from the endoscope image. 2. The control apparatus according to claim 1 , wherein the one or more processors are configured to identify propriety of recommendation of a special light observation for the estimated state of the diagnosis target organ. 3. The control apparatus according to claim 2 , wherein the one or more processors are configured to cause a display apparatus to collectively display the endoscopic image, information indicating a position of the lesion candidate region extracted, and information for urging implementation of the special light observation. 4. The control apparatus according to claim 1 , wherein the processor is further configured to identify an observation target site equivalent to an anatomical site of the diagnosis target organ included in the endoscopic image and identify a level of a lesion risk corresponding to the one abnormal symptom appearing in the observation target site. 5. The control apparatus according to claim 4 , wherein the processor is further configured to perform processing for setting sensitivity corresponding to the level of the lesion risk and causing the control apparatus to perform extraction of the lesion candidate region at the sensitivity. 6. The control apparatus according to claim 1 , wherein the one or more processors are configured to cause a display apparatus to collectively display the endoscopic image and information indicating a position of the lesion candidate region extracted. 7. A diagnosis support method comprising: identifying, based on physical information inputted, an estimated state of a diagnosis target organ of a subject; selecting a lesion extraction process associated with the estimated state of the diagnosis target organ from a plurality of different lesion extraction processes for extracting a lesion candidate region from an endoscopic image; and performing the lesion extraction process selected to extract the lesion candidate region from the endoscope image. 8. The diagnosis support method according to claim 7 , wherein the physical information comprises at least one of: information indicating a test result obtained by performing a test relating to the diagnosis target organ; information indicating a treatment history in the diagnosis target organ, information indicating a dose history of a drug relating to the diagnosis target organ; and information indicating presence or absence of a subjective symptom of the subject. 9. The diagnosis support method according to claim 7 , further comprising: identifying a level of a lesion risk in in the estimated state of the diagnosis target organ. 10. The diagnosis support method according to claim 9 , further comprising: setting sensitivity corresponding to the identified level of the lesion risk; and performing the lesion extraction process at the sensitivity set. 11. The diagnosis support method according to claim 7 , further comprising: identifying propriety of recommendation of a special light observation for the estimated state of the diagnosis target organ. 12. The diagnosis support method according to claim 11 , further comprising: controlling a display apparatus to collectively display the endoscopic image, information indicating a position of the lesion candidate region extracted, and information for urging implementation of the special light observation. 13. The diagnosis support method according to claim 7 , further comprising: identifying an observation target site equivalent to an anatomical site of the diagnosis target organ included in the endoscopic image; and identifying a level of a lesion risk corresponding to the estimated state of the diagnosis target organ appearing in the observation target site. 14. The diagnosis support method according to claim 13 , further comprising: setting sensitivity corresponding to the level of the lesion risk; and performing extraction of the lesion candidate region at the sensitivity. 15. The diagnosis support method according to claim 7 , further comprising: controlling a display apparatus to collectively display the endoscopic image and information indicating a position of the lesion candidate region extracted. 16. The diagnosis support method according to claim 7 , further comprising: setting sensitivity according to an instruction of a user; and performing the lesion extraction process at the sensitivity. 17. The diagnosis support method according to claim 7 , further comprising: identifying propriety of recommendation of a special light observation for the estimated state of the diagnosis target organ. 18. A computer-readable non-transitory recording medium recording a program, the program, when executed, cause one or more computers to execute: identifying, based on physical information inputted, an estimated state of a diagnosis target organ; selecting a lesion extraction process associated with the estimated state of the diagnosis target organ from a plurality of different lesion extraction processes for extracting a lesion candidate region from an endoscopic image; and performing the lesion extraction process selected to extract the lesion candidate region from the endoscope image. 19. The computer-readable non-transitory recording medium according to claim 18 , wherein the program, when executed, causes the one or more computers to execute: identify propriety of recommendation of a special light observation for the estimated state of the diagnosis target organ. 20. The computer-readable non-transitory recording medium according to claim 19 , wherein the program, when executed, causes the one or more computers to execute: control a display to collectively display the endoscopic image, information indicating a position of the lesion candidate region, and information for urging implementation of the special light observation.
Control therefor · CPC title
using light emitting diodes [LED] · CPC title
Control thereof · CPC title
Display arrangement · CPC title
for computer-aided diagnosis, e.g. based on medical expert systems · CPC title
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