Abstract: A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing reference deviation maps for a plurality of disease types. The reference deviation maps may include subsets of maps associated with severity levels of respective disease types, and a disease severity score may be associated with each severity level. The method may include selecting patient severity levels for multiple disease types based on the subsets of reference deviation maps. Also, the method may include automatically calculating a combined patient disease severity score based at least in part on the disease severity scores associated with the selected patient severity levels, and may include outputting a report based at least in part on the combined patient disease severity score. Additional methods, systems, and manufactures are also disclosed.

Abstract: A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing patient image and non-image deviation scores derived through respective comparisons of patient image and non-image data to standardized image and non-image data. The method may also include processing the image and non-image deviation scores to generate a visual output indicative of differences between the patient image and non-image data, and the standardized image and non-image data, respectively. Further, the method may include displaying the visual output. Additional methods, systems, and manufactures are also disclosed.

Abstract: A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing individual patient deviation maps indicative of a structural difference and a functional difference, respectively, of at least one anatomical region of a patient with respect to standardized reference image data. The method may also include generating a composite patient deviation map indicative of both the structural difference and the functional difference based on at least the individual patient deviation maps, and outputting the composite patient deviation map. Additional methods, systems, and manufactures are also disclosed.

Abstract: A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing patient deviation data of a structural difference between a patient anatomical feature and a standardized anatomical feature. The method may also include comparing the patient deviation data to reference deviation data sets representative of multiple disease types. Each reference deviation data set may be representative of an expected deviation from the standardized anatomical feature for a particular disease type. The method may further include automatically identifying one or more potential patient disease types based at least in part on the comparison. Additional methods, systems, and manufactures are also disclosed.

Abstract: A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing patient image and non-image deviation scores derived through respective comparisons of patient image and non-image data to standardized image and non-image data. The method may also include processing the image and non-image deviation scores to generate a visual output indicative of differences between the patient image and non-image data, and the standardized image and non-image data, respectively. Further, the method may include displaying the visual output. Additional methods, systems, and manufactures are also disclosed.

Abstract: A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing individual patient deviation maps indicative of a structural difference and a functional difference, respectively, of at least one anatomical region of a patient with respect to standardized reference image data. The method may also include generating a composite patient deviation map indicative of both the structural difference and the functional difference based on at least the individual patient deviation maps, and outputting the composite patient deviation map. Additional methods, systems, and manufactures are also disclosed.

Abstract: A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing patient deviation data of a structural difference between a patient anatomical feature and a standardized anatomical feature. The method may also include comparing the patient deviation data to reference deviation data sets representative of multiple disease types. Each reference deviation data set may be representative of an expected deviation from the standardized anatomical feature for a particular disease type. The method may further include automatically identifying one or more potential patient disease types based at least in part on the comparison. Additional methods, systems, and manufactures are also disclosed.

Abstract: A data processing technique is provided. In one embodiment, a computer-implemented method includes accessing reference deviation maps for a plurality of disease types. The reference deviation maps may include subsets of maps associated with severity levels of respective disease types, and a disease severity score may be associated with each severity level. The method may include selecting patient severity levels for multiple disease types based on the subsets of reference deviation maps. Also, the method may include automatically calculating a combined patient disease severity score based at least in part on the disease severity scores associated with the selected patient severity levels, and may include outputting a report based at least in part on the combined patient disease severity score. Additional methods, systems, and manufactures are also disclosed.