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Program Information

Visualization of Scans and Metrics for Longitudinal Informatics

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A Apte

A Apte*, H Veeraraghavan , N Tyagi , P Kijewski , J Deasy , Memorial Sloan Kettering Cancer Center, New York, NY


SU-E-J-213 (Sunday, July 12, 2015) 3:00 PM - 6:00 PM Room: Exhibit Hall

Purpose: To present new tools for visualizing scans across multiple timepoints alongwith changes in critical metrics.

Method: MR scans for a Lung cancer patient were acquired at four different timepoints. A display consisting of 2x2 panels was developed to show the four scans in Transverse, Sagittal or Coronal cut-planes. In order to make sure the user is looking at the same scan-section at different timepoints, two kinds of registration modes were built in: (1) Anatomical registration: Scans at different time points are rigidly registered to the first timepoint. Here, regular anatomical structures like bones are used to drive the registration. (2) Matching tumor mid-plane plane: In this mode the mid-planes of the tumors are matched to register the scans. This mode is useful to users who are interested in looking at the tumor shrinkage/growth longitudinally. Once image registration is performed according to the selected mode, the user can scroll across scan slices together at different timepoints. It is possible to make fine adjustments to the image registration by nudging a particular timepoint by few slices. It is also possible to evaluate the accuracy of registration by using the spotlight tool that highlights the region selected on one of the timepoints, on all the timepoints. Linear interpolation from the neighboring scan slices is used to display a cut-plane located in between slices. The visualization is further improved using the sinc upsampling filter. Once the scans at different timepoints are registered, it is possible to extract metrics for the structures of interest. Currently, statistical features and the first and second order texture features could be extracted at different timepoints.

Results: The new features and updates are built into CERR.

Conclusion: The tool developed would help visualize scans taken longitudinally along with providing insight into how the critical metrics change over time.

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