View source for 18058099. IMAGE PROCESSING APPARATUS simplified abstract (CANON KABUSHIKI KAISHA)

=IMAGE PROCESSING APPARATUS=


==Organization Name==

[[:Category:CANON KABUSHIKI KAISHA|CANON KABUSHIKI KAISHA]]


[[Category:CANON KABUSHIKI KAISHA]]

==Inventor(s)==

[[:Category:TSUYOSHI Kobayashi of Tokyo (JP)|TSUYOSHI Kobayashi of Tokyo (JP)]][[Category:TSUYOSHI Kobayashi of Tokyo (JP)]]

==IMAGE PROCESSING APPARATUS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18058099 titled 'IMAGE PROCESSING APPARATUS

==Simplified Explanation==

The abstract describes an image processing apparatus that reduces noise in radiation images captured by a radiation imaging apparatus. The apparatus obtains a first radiation image of an inspection target object and generates a second radiation image with reduced noise using a learned model.

* The image processing apparatus obtains a first radiation image captured by a radiation imaging apparatus.
* It generates a second radiation image with reduced noise compared to the first image.
* The noise reduction is achieved by inputting the first radiation image into a learned model.
* The learned model is obtained through learning using data that includes radiation images with simulated system noise.
* The simulated system noise is based on the manufacturing variation of the radiation imaging apparatus.

Potential applications of this technology:

* Medical imaging: The image processing apparatus can be used in medical imaging systems to enhance the quality of radiation images, improving diagnostic accuracy.
* Industrial inspection: The technology can be applied in industrial inspection systems to improve the clarity of radiation images, aiding in defect detection and quality control processes.

Problems solved by this technology:

* Noise reduction: The image processing apparatus addresses the issue of noise in radiation images, which can degrade image quality and affect the accuracy of analysis and interpretation.
* Manufacturing variation: By considering the manufacturing variation of the radiation imaging apparatus, the learned model can effectively reduce noise specific to each device, improving consistency and reliability.

Benefits of this technology:

* Improved image quality: The second radiation image generated by the apparatus has reduced noise, resulting in clearer and more detailed images for analysis and interpretation.
* Consistency across devices: By accounting for manufacturing variation, the learned model can be applied to different radiation imaging apparatuses, ensuring consistent noise reduction performance.
* Enhanced diagnostic accuracy: The noise reduction provided by the apparatus can improve the accuracy of diagnoses in medical imaging, leading to better patient care.


==Original Abstract Submitted==

An image processing apparatus includes an obtaining unit configured to obtain a first radiation image of an inspection target object that has been captured by a radiation imaging apparatus, and a generation unit configured to generate a second radiation image including noise reduced as compared with the first radiation image, by inputting the first radiation image obtained by the obtaining unit, to a learned model obtained by performing learning using learning data including a radiation image to which noise simulating system noise of a radiation imaging apparatus in accordance with a distribution that is based on a manufacturing variation of a radiation imaging apparatus is added.



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