Siemens Aktiengesellschaft

The General Hospital Corporation

Siemens Corporation

Herve Jun Alfred Lombaert

Yiyong Sun

Farida Cheriet

Leo John Grady

Frank Sauer

Chenyang Xu

Jonathan R Polimeni

Methods and systems determine a correspondence of two sets of data, each data set represents an object. A weighted graph is created from each data set, and a Laplacian is determined for each weighted graph, from which spectral components are determined. The spectral components determine a coordinate of a node in a weighted graph. Nodes of a weighted graph are weighted with a quantified feature related to anode. A coordinate related to a quantified feature of a node is added to the coordinate based on the spectral components. Spectral components related to a weighted graph are reordered to a common ordering. Reordered spectral components related to the first and second data set are aligned and a correspondence is determined. An object may be a brain and a feature may be a sulcal depth. Other objects for which a correspondence may be determined include an electrical network, an image and a social network.

Methods and systems for fast automatic brain matching via spectral correspondence

A method for segmenting at least a pair of regions of an image. High resolution data is obtained of the image. Each one of the pair of the regions in the image is marked. Graph cuts are used on the downsampled data to obtain first voxels along an outer boundary of a selected one of the pair of marked regions and second voxels along an inner boundary the selected region. The graphs cuts are projected to the previously obtained high-resolution image data. First and second sets of seeds are placed on the first voxels and a second set of seeds respectively. The first seeds grow into first areas extending inwardly of the selected region while simultaneously the second seeds grow into second areas extending towards the first extending areas until the first areas and the second areas meet to thereby establish the outer boundary of the selected region.

Fast 4D segmentation of large datasets using graph cuts

A method of performing 4-dimensional virtual endoscopy includes acquiring a sequence of cardiac images of a patient's heart from an imaging device; acquiring an electrocardiographic signal exhibiting cardiac cycles of the heart; and utilizing the electrocardiographic signal to gate the images for deriving respective 3-dimensional views in succession at corresponding cardiac cycles, from respective cardiac images at a selected phase point common to each of the corresponding cardiac cycles.

Method and apparatus for interactive 4-dimensional (4D) virtual endoscopy

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Montreal, Canada

Herve Jun Alfred Lombaert