| CPC A61B 5/02007 (2013.01) [A61B 5/0205 (2013.01); A61B 5/1075 (2013.01); A61B 5/489 (2013.01); G16H 20/10 (2018.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); A61B 5/055 (2013.01)] | 28 Claims |
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23. A method of assessing efficacy of a lung disease treatment, the method comprising:
obtaining, at a processor, a pre-treatment scan data set from a pre-treatment in vivo scan comprising a vasculature tree, wherein the pre-treatment in vivo scan is acquired in an absence of a contrast agent and is one of a fluoroscopy scan, an X-ray computer tomography (CT) scan, a four-dimensional CT (4D-CT) scan, a magnetic resonance imaging (MRI) scan, and an ultrasound scan;
obtaining, at the processor, a post-treatment scan data set from a post-treatment in vivo scan comprising the vasculature tree, wherein the post-treatment in vivo scan is acquired in an absence of a contrast agent and is one of a fluoroscopy scan, an X-ray computer tomography (CT) scan, a four-dimensional CT (4D-CT) scan, a magnetic resonance imaging (MRI) scan, and an ultrasound scan;
extracting, by the processor, blood vessel location data and blood vessel size data from the pre-treatment scan data set by:
applying a multi-scale filter to the pre-treatment scan data set at each of a plurality of single scales to provide for each single scale, a single scale probability field;
combining a plurality of the single scale probability fields to form an overall probability field and a scale field;
performing vessel segmentation on the overall probability field to extract a segmented vasculature tree; and
mapping the segmented vasculature tree to the scale field to quantify a geometry of the vasculature tree, wherein the geometry comprises blood vessel location data and blood vessel size data corresponding to diameter data; and
extracting, by the processor, blood vessel location data and blood vessel size data from the post-treatment scan data set by:
applying the multi-scale filter to the post-treatment scan data set at each of a plurality of single scales to provide for each single scale, a single scale probability field;
combining a plurality of the single scale probability fields to form an overall probability field and a scale field;
performing vessel segmentation on the overall probability field to extract a segmented vasculature tree; and
mapping the segmented vasculature tree to the scale field to quantify a geometry of the vasculature tree, wherein the geometry comprises blood vessel location data and blood vessel size data corresponding to diameter data;
selecting, by the processor, a region in the extracted blood vessel location data from either the pre-treatment scan data set or the post-treatment scan data set;
comparing, by the processor, the blood vessel size data associated with the blood vessel location data in the selected region to the blood vessel size data associated with the blood vessel location data of a corresponding region in the other scan data set; and
assessing the efficacy of the lung disease treatment based on the comparing.
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