Tomographic image reconstruction via machine learning
First Claim
1. A method of reconstructing an image from tomographic data obtained by an imaging process, the method comprising:
- performing at least one algorithm step on a raw data set or an intermediate data set of the tomographic data to obtain a final reconstructed image, wherein performing the at least one algorithm step comprises;
performing at least one conventional, non-deep-learning algorithm on a raw data of the tomographic data to obtain an intermediate data set of an initial reconstructed image; and
performing a deep learning algorithm on the intermediate data set to obtain the final reconstructed image.
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Abstract
Tomographic/tomosynthetic image reconstruction systems and methods in the framework of machine learning, such as deep learning, are provided. A machine learning algorithm can be used to obtain an improved tomographic image from raw data, processed data, or a preliminarily reconstructed intermediate image for biomedical imaging or any other imaging purpose. In certain cases, a single, conventional, non-deep-learning algorithm can be used on raw imaging data to obtain an initial image, and then a deep learning algorithm can be used on the initial image to obtain a final reconstructed image. All machine learning methods and systems for tomographic image reconstruction are covered, except for use of a single shallow network (three layers or less) for image reconstruction.
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Citations
20 Claims
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1. A method of reconstructing an image from tomographic data obtained by an imaging process, the method comprising:
performing at least one algorithm step on a raw data set or an intermediate data set of the tomographic data to obtain a final reconstructed image, wherein performing the at least one algorithm step comprises; performing at least one conventional, non-deep-learning algorithm on a raw data of the tomographic data to obtain an intermediate data set of an initial reconstructed image; and performing a deep learning algorithm on the intermediate data set to obtain the final reconstructed image. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
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15. A system for reconstructing an image from raw data obtained by a medical imaging process, the system comprising:
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a subsystem for obtaining tomographic imaging data; at least one processor; and a machine-readable medium, in operable communication with the subsystem for obtaining tomographic imaging data and the at least one processor, having machine-executable instructions stored thereon that, when executed by the at least one processor, perform at least one algorithm step on a raw data set or an intermediate data set of the tomographic data to obtain a final reconstructed image; wherein the at least one algorithm step comprises; performing at least one conventional, non-deep-learning algorithm on a raw data of the tomographic data to obtain an intermediate data set of an initial reconstructed image; and performing a deep learning algorithm on the intermediate data set to obtain the final reconstructed image. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification