Image processing apparatus, image processing method, and computer-readable medium
An image processing apparatus is provided that includes: an obtaining unit is configured to obtain a first radiation image of an object to be examined; and a generating unit configured to, by inputting the first radiation image obtained by the obtaining unit into a learned model, generate a second radiation image in which noise is reduced compared to the first radiation image, wherein the learned model is obtained by training using training data that includes a radiation image obtained by adding noise with attenuated high-frequency components.
1 . An image processing apparatus, comprising:
a processor; and
a memory, including instructions stored thereon, which when executed by the processor, cause the image processing apparatus to:
obtain a first radiation image of an object to be examined; and
by inputting the first radiation image into a learned model, generate a second radiation image in which noise is reduced compared to the first radiation image, wherein the learned model is obtained by training using training data including a radiation image obtained by adding noise with reduced high-frequency components compared to low-frequency components,
wherein the first radiation image is obtained by a radiation detector including a scintillator.
2 . The image processing apparatus according to claim 1 , wherein the second radiation image is generated by inputting the first radiation image into a learned model obtained by training using training data including a radiation image obtained by adding the noise with reduced high-frequency components according to a modulation transfer function of a scintillator included in a radiation detector.
3 . The image processing apparatus according to claim 1 , wherein the second radiation image is generated by inputting the first radiation image into a learned model obtained by training using training data including a radiation image obtained by adding artificial noise including noise simulating system noise of a radiation detector and the noise with reduced high-frequency components.
4 . The image processing apparatus according to claim 3 , wherein the artificial noise includes noise obtained by compositing, at a predetermined compositing ratio, the noise simulating system noise of a radiation detector and the noise with reduced high-frequency components.
5 . The image processing apparatus according to claim 4 , wherein the second radiation image is generated by inputting the first radiation image into a learned model obtained by training using training data including a radiation image obtained by adding artificial noise obtained by compositing, at a first compositing ratio, the noise simulating system noise of a radiation detector and the noise with reduced high-frequency components, and a radiation image obtained by adding artificial noise obtained by compositing, at a second compositing ratio that is different from the first compositing ratio, the noise simulating system noise of the radiation detector and the noise with reduced high-frequency components.
6 . The image processing apparatus according to claim 3 , wherein an average value or a median of the artificial noise is 0.
7 . The image processing apparatus according to claim 1 , wherein the instructions, when executed by the processor, further cause the image processing apparatus to:
perform transform processing on a radiation image of an object to be examined so as to stabilize a variance of noise that follows a Poisson distribution which is included in the radiation image of the object to be examined,
wherein:
the transform processing is performed on the first radiation image;
the second radiation image is generated based on the first radiation image on which the transform processing is performed; and
inverse-transform processing of the transform processing is performed on the second radiation image.
8 . The image processing apparatus according to claim 7 , wherein the training data includes a radiation image obtained by performing the transform processing on a radiation image of an object to be examined.
9 . The image processing apparatus according to claim 1 , wherein the training data includes data in which a radiation image obtained by adding the noise to a radiation image of an object to be examined is set as input data, and a radiation image of an object to be examined is set as ground-truth.
10 . The image processing apparatus according to claim 7 , wherein the training data includes data in which a radiation image obtained by performing the transform processing on a radiation image of an object to be examined to which the noise is added is set as input data, and a radiation image obtained by performing the transform processing on a radiation image of an object to be examined is set as ground-truth.
11 . The image processing apparatus according to claim 1 , wherein the instructions, when executed by the processor, further cause the image processing apparatus to:
divide a radiation image into a plurality of radiation images of regions,
wherein:
a radiation image of an object to be examined is divided into a plurality of first radiation images;
a plurality of second radiation images is generated based on the plurality of first radiation images; and
the plurality of second radiation images is combined to generate a third radiation image in which noise is reduced.
12 . The image processing apparatus according to claim 1 , wherein a radiation image that is used in the training data includes a plurality of radiation images of regions obtained by dividing a radiation image of an object to be examined.
13 . The image processing apparatus according to claim 1 , wherein generating the second radiation image includes:
transforming the first radiation image according to a ratio of a modulation transfer function of a scintillator included in a radiation detector used to obtain the first radiation image with respect to a modulation transfer function of the scintillator included in the radiation detector used to obtain a radiation image of an object to be examined that is used in the training data;
generating the second radiation image from the transformed first radiation image using the learned model; and
transforming the second radiation image according to an inverse of the ratio.
14 . The image processing apparatus according to claim 1 , wherein the learned model includes a neural network including a U-shaped configuration that has an encoder function and a decoder function, and the neural network has an adding layer configured to add input data to data that is output from a first convolutional layer on a decoder side.
15 . An image processing apparatus comprising:
a processor; and
a memory, including instructions stored thereon, which when executed by the processor, cause the image processing apparatus to:
obtain a first radiation image of an object to be examined; and
by inputting the first radiation image into a learned model, generate a second radiation image in which noise is reduced compared to the first radiation image, wherein the learned model is obtained by training using training data including a radiation image obtained by adding noise of which noise amount of high-frequency components is smaller than noise amount of low-frequency components,
wherein the first radiation image is obtained by a radiation detector including a scintillator.
16 . An image processing method, comprising:
obtaining a first radiation image of an object to be examined; and
generating, by inputting the obtained first radiation image into a learned model, a second radiation image in which noise is reduced compared to the first radiation image, wherein the learned model is obtained by training using training data that includes a radiation image obtained by adding noise with reduced high-frequency components compared to low-frequency components,
wherein the first radiation image is obtained by a radiation detector including a scintillator.
17 . A non-transitory computer-readable medium having stored thereon a program that, when executed by a computer, causes the computer to execute respective steps of the image processing method according to claim 16 .
18 . An image processing method comprising:
obtaining a first radiation image of an object to be examined; and
generating, by inputting the first radiation image into a learned model, generate a second radiation image in which noise is reduced compared to the first radiation image, wherein the learned model is obtained by training using training data including a radiation image obtained by adding noise of which noise amount of high-frequency components is smaller than noise amount of low-frequency components, wherein the first radiation image is obtained by a radiation detector including a scintillator.
19 . A non-transitory computer-readable medium having stored thereon a program that, when executed by a computer, causes the computer to execute respective steps of the image processing method according to claim 18 .