ChangeTracker:Lupus DBP

This page summarizes requirements for longitudinal lesion analysis for Lupus DBP, and resulting discussion on possible modifications required to ChangeTracker to make it possibly a more generic change analysis tool.

Longitudinal lesion analysis for Lupus project

Lupus DBP will face the need of analyzing multi-modal same-subject brain imaging data at 3+ timepoints in order to detect white matter lesions and analyze their progression. At each time point the following data will be available:

• T1
• T2
• FLAIR
• results of lesion classification: (1) labeled connected component filtering of classification/segmentation output + (2) per-label threshold information for each of the connected components

Essentially, pre-thresholded classification output is the per-pixel estimation of likelihood that the pixel belongs to the lesion. Threshold is defined on the per-lesion basis, since its selection depends on the tumor location and other properties.

Requirements to the analysis results are:

• ability to accept multiple lesions, but give control over per-lesion analysis
• ability to go through the available lesion modalities
• CompareView mode for rsults visualization
• naturally, no need for lesion detection functionality
• ability to adjust the classification threshold (per-lesion)
• distance-based coloring of the change results