Method and apparatus for generating quantitative data for biliary tree structures
Inventors
Vikal, Siddharth • Brady, John Michael
Assignees
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Publication Number
US-10846847-B2
Publication Date
2020-11-24
Expiration Date
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.
Core Innovation
The invention generates quantitative data for biliary tree structures from volumetric medical imaging scan data by performing tubular enhancement to derive at least one tubeness measure for each voxel and using the tubeness measure to perform segmentation of the volume. The segmentation identifies tubular biliary structures within the volume based at least partly on the tubeness measure for each voxel. Quantitative biliary tree data are output based on quantitative structural parameters computed for segmented tubular biliary structures.
For each segmented tubular biliary structure, the invention computes quantitative structural parameters for at least one location along the length of the tubular biliary structure. The quantitative structural parameters include information representing a center-line and parameters along the tubular length. The center-line representation is modeled using hierarchical parametric modeling with starting/ending centre-line points and successive centre-line points derived from viable successor points evaluated with a cost function, followed by cleanup/centring and determining tube width along the center-line.
The invention detects additional structural and pathological information from the quantitative tubular model, including branching nodes and a hierarchical biliary tree model. Branch nodes are identified by masking the current duct and searching an annulus for locations of branching nodes. Tube-width–based detection and quantification of strictures, dilatations, and beading is derived from tube-width patterns, and topological tortuosity metrics such as distance and inflection count are computed using a Frenet-Serret frame, including sum of angles. Inflammation and fibrosis are optionally detected by registering MRCP-derived biliary structure to T1 data using segmented gallbladder as a landmark.
Claims Coverage
The document includes two independent claims: a method for generating quantitative biliary-tree data and an image processing system for performing the same generating pipeline. The independent claims share a common inventive core consisting of tubular enhancement producing per-voxel tubeness, tubeness-based segmentation of tubular biliary structures, computation of quantitative structural parameters along the segmented tube length, and output of quantitative biliary tree data.
Per-voxel tubular enhancement to derive tubeness measures
performing tubular enhancement on the volumetric medical imaging scan data to derive at least one tubeness measure for each voxel within the volumetric medical imaging scan data
Tubeness-based segmentation of tubular biliary structures
performing segmentation of a volume of the medical imaging scan data to identify tubular biliary structures within the volume of the medical imaging scan data based at least partly on the at least one tubeness measure for each voxel
Quantitative structural parameters along segmented tubular length
for at least one segmented tubular biliary structure within the volume of the medical imaging scan data, computing at least one set of quantitative structural parameters for at least one location along the length of the tubular biliary structure
Output of quantitative biliary tree data
outputting quantitative biliary tree data comprising the at least one set of quantitative structural parameters for the at least one segmented tubular biliary structure
Processing-device implementation of generating quantitative biliary tree data
perform tubular enhancement on the volumetric medical imaging scan data to derive at least one tubeness measure for each voxel within the volumetric medical imaging scan data; perform segmentation of a volume of the medical imaging scan data to identify tubular biliary structures within the volume of the medical imaging scan data based at least partly on the at least one tubeness measure for each voxel; for at least one segmented tubular biliary structure within the volume of the medical imaging scan data, compute at least one set of quantitative structural parameters for at least one location along the length of the tubular biliary structure; and output quantitative biliary tree data comprising the at least one set of quantitative structural parameters for the at least one segmented tubular biliary structure
Across the independent claims, coverage centers on generating quantitative biliary tree data by deriving per-voxel tubeness through tubular enhancement, segmenting tubular biliary structures using the tubeness measure, computing quantitative structural parameters at locations along the segmented tubular length, and outputting the resulting quantitative biliary tree data. The second independent claim implements the same generating pipeline as an image processing system arranged to perform these steps with at least one processing device.
Stated Advantages
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