Reconstruction of Blood Vessel Trees from Visible Human Data Zhenrong Qian and Linda Shapiro Computer Science & Engineering.

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Presentation transcript:

Reconstruction of Blood Vessel Trees from Visible Human Data Zhenrong Qian and Linda Shapiro Computer Science & Engineering Department University of Washington

Introduction Goal Computer vision to reconstruct the blood vessels of the lungs from Visible Human Data Computer vision semi-automation low-level image processing model construction

Visible Human Data: Slice through the Lung

Problems Encountered Data source Characteristics of blood vessels black spots that are not blood vessels variations of lighting Characteristics of blood vessels similar color surrounds lack of knowledge close location shape variety continuous change not expected dense data

Finding the contours of a vessel being tracked (1) Previous contour Current slice EM Segmentation False color for the segmentation

Finding the contours of a vessel being tracked (2) The results after selecting regions of similar color to the tracked region Segmentation result Selected regions

Finding the contours of a vessel being tracked (3) The results after selecting the region that overlaps most with the previous contour Region that overlaps most Selected regions

Find the contours of a vessel being tracked (4) The results after morphology to close holes and remove noise Selected region After noise removal

Find the contours of a vessel being tracked (5) The contour is determined through a fast-marching level-set approach Previous contour Current contour

How branching is handled One contour divides into two Two contours merge into one

The use of resampling when the axis is not vertical Track the axis through the center points of found contours Fit a spline curve Resample the data perpendicular to the spline curve Use the resampled contours for model creation

Detect the axis Center points of found contours Spline-fitted axis

Resample the data perpendicular to the spline curve

Overall Procedure for finding Vessel Trees The user selects a starting point The program automatically tracks the selected vessel and any branches it finds The program creates a generalized cylinder representation of the vessel tree The user may select more starting points

Some Initial Results Artery tree from single seed Vein tree from single seed

Typical Cross Section

Results : blood vessels in right lung from previous section