http://rdf.ncbi.nlm.nih.gov/pubchem/patent/WO-2021155123-A1

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filingDate 2021-01-29-04:00^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_38f1222f33b7b03a471e834674b299e8
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publicationDate 2021-08-05-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber WO-2021155123-A1
titleOfInvention Systems and methods for artifact reduction in tomosynthesis with deep learning image processing
abstract Systems and methods are provided for a deep learning-based digital breast tomosynthesis (DBT) image reconstruction that mitigates limited angular artifacts and improves in-depth resolution of the resulting images. The systems and methods may reduce the sparse -view artifacts in DBT via deep learning without losing image sharpness and contrast. A deep neural network may be trained in a way to reduce training-time computational cost. An ROI loss method may be used for further improvement on the resolution and contrast of the images.
priorityDate 2020-01-31-04:00^^<http://www.w3.org/2001/XMLSchema#date>
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Total number of triples: 25.