The LOSSST algorithm

An example query:

example lossst query

The underlying mechanism:

lossst explanation

The query region is defined by a user on an EMAP virtual embryo model (in this case TS11 - shown in magenta). The LOSSST algorithm initially dilates 30 pixels (or voxels for 3D queries) from the edge of the user defined region to define a local comparison region on the virtual embryo model (indicated by the dashed line). All spatial annotations for EMAGE database entries that have been annotated to the same model are then spatially compared to the query region using the Jaccard Index, but only within the local comparison region. Jaccard Index similarity coefficient scores are calculated using Woolz functions. A Jaccard Index similarity coefficient score of 1 indicates exact spatial similaity between the query region and the mapped pattern. Progressively smaller Jaccard Index similarity coefficient scores indicate patterns that are progressively less spatially similar. Note that for the purpose of simplicity, this example only displays the 9 most similar patterns out of 50+ patterns that intersect with the query region, and does not show the least spatially similar 40+ patterns.


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