Automated anatomical labeling by multi-contrast diffeomorphic probability fusion
A computer-implemented method, system and non-transitory computer readable storage medium for classifying a region of interest of a subject, including receiving imaging data comprising at least one image element, the imaging data comprising the region of interest of the subject; providing a pluralit...
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| Format | Patent |
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| Language | English |
| Published |
14.01.2020
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| Online Access | Get full text |
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| Abstract | A computer-implemented method, system and non-transitory computer readable storage medium for classifying a region of interest of a subject, including receiving imaging data comprising at least one image element, the imaging data comprising the region of interest of the subject; providing a plurality of atlases, each of the plurality of atlases having a candidate region that corresponds to the region of interest of the imaging data, each of the plurality of atlases having at least one image element with associated location and property information; co-registering the plurality of atlases to the imaging data, using at least one processor; assigning a probability to generate a labeling parameter for the region of interest, the probability being associated with each atlas; and classifying the region of interest of the subject based on the assigning. |
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| AbstractList | A computer-implemented method, system and non-transitory computer readable storage medium for classifying a region of interest of a subject, including receiving imaging data comprising at least one image element, the imaging data comprising the region of interest of the subject; providing a plurality of atlases, each of the plurality of atlases having a candidate region that corresponds to the region of interest of the imaging data, each of the plurality of atlases having at least one image element with associated location and property information; co-registering the plurality of atlases to the imaging data, using at least one processor; assigning a probability to generate a labeling parameter for the region of interest, the probability being associated with each atlas; and classifying the region of interest of the subject based on the assigning. |
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| References | Akinyemi et al. (2012/0177263) 20120700 Rueckert et al. (2012/0281900) 20121100 Kiraly (8170330) 20120500 Liu (2015/0086096) 20150300 Schreibmann (2011/0235884) 20110900 Pekar (2012/0320055) 20121200 |
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| Title | Automated anatomical labeling by multi-contrast diffeomorphic probability fusion |
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