Description

Great…yet another TMA dearray program. What does this one do? Coreograph uses UNet, a deep learning model, to identify complete/incomplete tissue cores on a tissue microarray. It has been trained on 9 TMA slides of different sizes and tissue types.

Input

Name (Type)
Description
Pattern

image (file)

ome.tif/tif file

*.{ome.tif,tif}

meta (map)

Groovy Map containing sample information

Output

Name (Type)
Description
Pattern

versions (file)

File containing software versions

versions.yml

cores (file)

Complete/Incomplete tissue cores

*.{tif}

masks (file)

Binary masks for the Complete/Incomplete tissue cores

./masks/*.{tif}

tma_map (file)

A TMA map showing labels and outlines

TMA_MAP.tif

centroids (file)

A text file listing centroids of each core in format Y, X

centroidsY-X.txt

meta (map)

Groovy Map containing sample information

included in
mcmicro
maintainers
Github user arozhada
Github user MargotCh
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Tools

coreograph
MIT License

A TMA dearray porgram that uses UNet, a deep learning model, to identify complete/incomplete tissue cores on a tissue microarray.

mcmicro.org/parameters/core.html#coreograph mcmicro.org/troubleshooting/tuning/coreograph https://github.com/HMS-IDAC/UNetCoreograph 10.1038/s41592-021-01308-y