Tissue Microarray Auto De-Array

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

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

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

Then, extract de-arrayed cores automatically.

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

-q quality of JPEG images to be saved.