Matt:LabNotes/2014-8-20
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Decoding PGP1F with Agi26k0gap Rolonies Using PISA Mask[edit]
- Images saved in: Dropbox\GradZhangLab\FullDecoding_v1
- First did Max Intensity Projection of the 21 images
- 7 cycles each with 3 color channels (Cycle1-488, Cycle1-Cy3, Cycle1-Cy5, Cycle2-488,...)
- Then used PISA on MIP image to identify all secondary rolonies
Use: PISA Gui v1: 6870 rolonies DataFileFilter = '*_20x_4k_*.tif'; PISAParam.log_radius = 2; PISAParam.log_upper = -5e-4; PISAParam.area_upper = 50; PISAParam.area_lower = 9; PISAParam.axratio_lower = 0.5; PISAParam.circ_upper = 1.6; PISAParam.circ_lower = 0.8; PISAParam.pconn = 8; PISAParam.bkgmult_lower = 3;
v2: 4030 rolonies DataFileFilter = '*_20x_4k_*.tif'; PISAParam.log_radius = 3; PISAParam.log_upper = -2e-4; PISAParam.area_upper = 100; PISAParam.area_lower = 4; PISAParam.axratio_lower = 0.6; PISAParam.circ_upper = 1.6; PISAParam.circ_lower = 0.8; PISAParam.pconn = 8; PISAParam.bkgmult_lower = 7;
v3: 4658 rolonies DataFileFilter = '*_20x_4k_*.tif'; PISAParam.log_radius = 3; PISAParam.log_upper = -2e-5; PISAParam.area_upper = 144; PISAParam.area_lower = 16; PISAParam.axratio_lower = 0.6; PISAParam.circ_upper = 1.6; PISAParam.circ_lower = 0.8; PISAParam.pconn = 8; PISAParam.bkgmult_lower = 4;
Use: Rolony_Counting_Batch_8a.m v4: 4382 rolonies DataFileFilter = '*_20x_4k_*.tif'; PISAParam.log_radius = 3; PISAParam.log_upper = -2e-5; PISAParam.area_upper = 144; PISAParam.area_lower = 16; PISAParam.axratio_lower = 0.6; PISAParam.circ_upper = 1.6; PISAParam.circ_lower = 0.8; PISAParam.pconn = 8; PISAParam.bkgmult_lower = 4;
v5: 4382 rolonies (same as v4 so deleted) DataFileFilter = '*_20x_4k_*.tif'; PISAParam.log_radius = 3; PISAParam.log_upper = -2e-4; PISAParam.area_upper = 144; PISAParam.area_lower = 16; PISAParam.axratio_lower = 0.6; PISAParam.circ_upper = 1.6; PISAParam.circ_lower = 0.8; PISAParam.pconn = 8; PISAParam.bkgmult_lower = 3;
- Used bwimage from PISA to mask each of the 21 images and then regionprops to obtain MeanIntensity, Area, and Centroid values for each feature
- There were 4370 features identified
- Used PISA_MaskImages.m