Presented by
Saloni Goel

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Cardiac CT Angiography Image Reconstruction
Introduction
The use of Content Adaptive Mesh model(CAMM) for Cardiac CT reconstruction is explored.
Cardiac CT Angiography images are being reconstructed.
Content-Adaptive Mesh Generation
Mesh modeling of an image involves partitioning the image into a collection of non-overlapping (generally polygon) patches, called mesh elements.
With a mesh model one can strategically place the mesh nodes more densely in regions containing significant features.
Sample Cardiac CT Angiography Image
Steps in Image Reconstruction
Image is filtered using the Canny Edge Detection algorithm
Floyd- Steinberg Error Diffusion algorithm is applied for the placement of mesh nodes.
Mesh nodes are connected using Delaunay Triangulation algorithm.
Iterative Reconstruction algorithms are applied so as to get the reconstructed image.
Feature Map Extraction
Second derivatives are used for calculating the feature vector at any pixel.
Then the following formulae is used to compute the feature map
Canny Edge Detection Algorithm
preserving useful structural information about object.
good detection
the algorithm marks as many real edges in the image as possible.
good localization
edges marked are as close as possible to the edge in the real image.
minimal response
a given edge in the image should only be marked once, and where possible, image noise should not create false edges.
Our Finding
We found that instead of using linear filtering i.e., second derivatives for filtering the image, the Canny Edge detection algorithm is far better to bring out the specific details about the image.
Adaptive Mesh- Node Placement
Modified Floyd- Steinberg error diffusion algorithm used.
Used for digital half-toning.
Helps in placement of mesh nodes in accordance with the spatial density specified by the feature map .
Delaunay Triangulation algorithm
Connects a given set of mesh nodes.
the circle circumscribing any triangular element contains only the nodal points belonging to that triangle
yields a well-structured mesh at a reasonable computational cost
Reconstruction of Image
Iterative reconstruction algorithms applied.
Maximum Likelihood and Maximum a Posteriori (MAP) algorithms being used for reconstructing the image with the help of the Content Adaptive Mesh Model
Results
Future Work
We will extend the Reconstruction technique used here for reconstructing the 3D Cardiac CT Angiography Images.
The 3D reconstructed image will help visualize the affected area more clearly.
Which in turn will help in better diagnosis of the coronary blockage.