/TMA-ADA

Tissue Microarray Auto De-Array

Primary LanguagePython

Tissue Microarray Auto De-Array

A python script for spliting & extracting cores from TMA slides automatically.

image

requirements

Only pandas, numpy, pillow and py-opencv need to be installed.

install using anaconda

conda install pandas numpy pillow py-opencv -c conda-forge

or pip

pip install pandas numpy pillow opencv-python

It works better with gdal .

install using anaconda

conda install osgeo -c conda-forge

or pip

pip install osgeo

usage

de-array

Automatically de-array with at least only one parameter:

python ada.py demo/ST221.jpg -c 6

Specific more parameters to get better performance.

-d core diameter in pixels

-c number of columns

-r number of rows

You can edit the .csv file to correct unexcept results.

name col row x y w h QC_pass
A1 0 0 0 18 251 260 True
A2 0 1 0 287 246 257 True
A3 0 2 0 546 241 255 True
A4 0 3 0 815 241 255 True
B1 1 0 267 2 249 268 True
B2 1 1 261 280 248 244 True
B3 1 2 255 538 244 272 True
B4 1 3 255 821 248 249 True
C1 2 0 523 0 253 259 True
C2 2 1 518 273 260 268 True
C3 2 2 513 543 253 271 True
C4 2 3 513 818 251 252 True
D1 3 0 783 0 250 261 True
D2 3 1 783 271 258 266 True
D3 3 2 780 547 255 254 True
D4 3 3 778 815 252 255 True
E1 4 0 1045 0 262 266 True
E2 4 1 1045 270 262 271 True
E3 4 2 1043 547 257 252 True
E4 4 3 1041 801 253 269 True
F1 5 0 1312 0 267 266 False
F2 5 1 1312 269 267 289 True
F3 5 2 1309 560 260 225 False
F4 5 3 1307 787 254 283 True

extract

Then, extract de-arrayed cores automatically.

python extract.py demo/ST221.jpg -q 30

-q quality of JPEG images to be saved.