We note that given the size of an IBF entry, the average size of a set element and an estimate of the size overlap, near-perfect thresholds (instead of the 50%-heuristic we described earlier) can be trivially computed.
The column between the dendrogram and the heatmap represents the probesets either differentially expressed and selected with the 70% perfect alignment threshold (yellow), or the probesets differentially expressed but not selected by the Perfect Alignment threshold (black).
However, the following Theorem 1 will prove that a0,a1,b0,b1 leak no information about the secret at all, and the proposed scheme is a perfect (k,n) threshold secret image sharing scheme that satisfies the threshold property.
Depending on the sequence technique and the signal intensity of the lesions and given that conditions are optimal (i.e. patient can keep a breath-hold for 20 s or perfect gating/triggering), a threshold size of 3-4 mm can be assumed for lung nodule detection with MRI [19, 20].
For a perfect test, a threshold t could be chosen such that all individuals with a score larger than t develop the condition, and all individuals with a score less than t don't.
We used a hierarchical clustering method to concisely represent the expression profiles of all the 1,854 differentially expressed probesets, and the intersection between these probesets and those selected by matching tomato vs. potato at a 70% perfect alignment (%_PERF_ALIGN) threshold.
