Abstract: A method (200) and apparatus (1100) for generating quantitative data for biliary tree structures from volumetric medical imaging scan data. The method comprises performing segmentation (230; 300) of a volume of the medical imaging scan data to identify tubular biliary structures within the volume of the medical imaging scan data; for at least one segmented tubular biliary structure within the volume of the medical imaging scan data, computing (240; 800) at least one set of quantitative structural parameters for at least one location along the length of the tubular biliary structure; and outputting (250) quantitative biliary tree data comprising the at least one set of quantitative structural parameters for the at least one segmented tubular biliary structure.

Abstract: A method (200) and apparatus (1100) for generating quantitative data for biliary tree structures from volumetric medical imaging scan data. The method comprises performing segmentation (230; 300) of a volume of the medical imaging scan data to identify tubular biliary structures within the volume of the medical imaging scan data; for at least one segmented tubular biliary structure within the volume of the medical imaging scan data, computing (240; 800) at least one set of quantitative structural parameters for at least one location along the length of the tubular biliary structure; and outputting (250) quantitative biliary tree data comprising the at least one set of quantitative structural parameters for the at least one segmented tubular biliary structure.

Abstract: A method and apparatus for generating a data profile for a medical scan. The method comprises obtaining data point values for a plurality of data points representing spatial locations within the medical scan, determining data point classification parameters defining data point value ranges for a plurality of classes, assigning each data point to a class having a data point value range corresponding to the value for that data point, generating a data profile for the medical scan based at least partly on the assignment of the data points to classes, and outputting the generated data profile for the medical scan.

Abstract: The present application discloses a technique for targeting therapeutic thermal energy to human tissue that is subject to displacement during a respiratory cycle using ARMA modeling. It discloses using an ARMA treatment of MRI tracking data of salient features of the tissue of interest to predict the spacial position of the portion of the tissue to be treated and using this prediction to guide the application of the thermal energy. It also discloses that this technique is particularly useful when the tissue of interest undergoes elastic deformation in a respiratory cycle and high energy focused ultrasound (HIFU) is used to ablate diseased tissue such as a cancerous tumor.

Abstract: The present application discloses a technique for targeting therapeutic thermal energy to human tissue that is subject to displacement during a respiratory cycle using ARMA modeling. It discloses using an ARMA treatment of MRI tracking data of salient features of the tissue of interest to predict the spacial position of the portion of the tissue to be treated and using this prediction to guide the application of the thermal energy. It also discloses that this technique is particularly useful when the tissue of interest undergoes elastic deformation in a respiratory cycle and high energy focused ultrasound (HIFU) is used to ablate diseased tissue such as a cancerous tumor.