Medical image processing device, endoscope system, medical image processing method, and program
There are provided a medical image processing device, an endoscope system, a medical image processing method, and a program which detect an optimal lesion region according to an in-vivo position of a captured image. Images at a plurality of in-vivo positions of a subject are acquired from medical equipment that sequentially captures and displays in real time the images; positional information indicating the in-vivo position of the acquired image is acquired; from among a plurality of region-of-interest detection units that detect a region of interest from an input image and correspond to the plurality of in-vivo positions, respectively, a region-of-interest detection unit corresponding to the position indicated by the positional information is selected; and the selected region-of-interest detection unit detects a region of interest from the acquired image.
1. An endoscope system comprising:
an endoscope configured to be inserted into a body cavity of a subject; and one or more processors configured to:
acquire images at in-vivo positions of the subject by sequentially capturing the images through the endoscope;
acquire positional information indicating the in-vivo positions of the acquired images;
select a learned model that is a model learned using images corresponding to a position indicated by the acquired positional information among a plurality of learned models that are models learned using data sets including images at different in-vivo positions respectively and are configured to detect a region of interest;
cause the selected learned model to detect a region of interest in the acquired images;
and cause a display to display the position indicated by the acquired positional information, wherein-the learned models are models learned using data sets including images of mucous membranes at different in-vivo positions, respectively.
2. The endoscope system according to claim 1 , wherein the one or more processors are further configured to cause the display to display a schematic diagram of the subject and a figure on the schematic diagram at the position indicated by the acquired positional information.
3. The endoscope system according to claim 2 , wherein the processors are further configured to cause the display to display one of the acquired images corresponding to the position indicated by the acquired positional information, together with the schematic diagram and the figure.
4. The endoscope system according to claim 3 , wherein the schematic diagram is of a lumen of the subject.
5. The endoscope system according to claim 1 , wherein the processors are further configured to recognize the in-vivo positions from the acquired images.
6. The endoscope system according to claim 1 , wherein the processors are further configured to receive the positional information through a user's input.
7. The endoscope system according to claim 6 , wherein:
the endoscope is configured to be inserted from a mouth or a nose of the subject; and
the processors are configured to receive the positional information indicating at least one of positions of a pharynx, an esophagus, a stomach and a duodenum of the subject.
8. The endoscope system according to claim 6 , wherein:
the endoscope is configured to be inserted from an anus of the subject; and
the processors are configured to receive the positional information indicating at least one of positions of a rectum, a sigmoid colon, a descending colon, a transverse colon, an ascending colon, a cecum, an ileum and a jejunum of the subject.
9. The endoscope system according to claim 1 , wherein the positional information is acquired by an endoscope insertion shape observation device or by irradiating the subject with X-rays from an outside.
10. The endoscope system according to claim 1 , wherein:
the processors are further configured to recognize the in-vivo positions from the acquired images by means of the learned models; and
the in-vivo positions include positions of a mouth, a pharynx, an esophagus, a stomach, and a duodenum of the subject.
11. The endoscope system according to claim 1 , wherein the processors are configured to chronologically capture the images at the in- vivo positions.
12. The endoscope system according to claim 11 , wherein the processors are configured to capture the images at a fixed frame rate.
13. The endoscope system according to claim 1 , further comprising a storage,
wherein the processors are further configured to cause the storage to store the acquired image containing the region of interest and the positional information associated with each other.
14. The endoscope system according to claim 1 , wherein the learned models are configured to detect a lesion region as the region of interest.
15. The endoscope system according to claim 1 , wherein the processors are further configured to cause the display to display the positional information.
16. The endoscope system according to claim 1 , wherein: the endoscope includes an imaging sensor; and the processors are configured to capture the images through the imaging sensor.
17. The endoscope system according to claim 1 , wherein the processors are further configured to cause the display to display the region of interest detected by the selected learned model.
18. The endoscope system according to claim 17 , wherein the region of interest is polyp, cancer, inflammation, or vascular atypia.