Back to COCO 2: A less minimalistic 125 images +json dataset

125 grey scaled images were chosen from a previous dataset available on github.

An annotation file was generated by hand online with makesense.ai and saved as a unique json file in COCO format. This small dataset is freely available as an archive.

Check annotation file validity with pycococreator.

Pycococreator by Waspinator was used to display the annotations  (aka the segmentation) over a grey scaled image in the following jupyter notebook 

 

validating de facto the annotation file produced with makesense.ai:

Data registration in detectron2:

This  is the next step.

The idea is to follow the tutorial on custom dataset registration, possibly using the balloons example by davamix.

Karyotype of ten fibroblasts after Alu sequences and telomeres hybridization

The image bellow  was obtain after sequential hybridization of telomeric PNA probe (FITC:green) followed by hybridization of Alu-PCR product (Rhodamin: Red):

Pairs of chromosomes are ordered by columns from HSA 1 (left) to XY (right) . Metaphases are ordered by row.

Image acquisition was performed with a low resolution 8bits camera mounted on a Leica DMRB fluorescence microscope (100x). Raw images were transferred from a Unix Cytovision station with 3 inch 1/2 floppy disk to a power Macintosh 9500.

Example of a metaphase after alignment of Alu image on DAPI / telomeres images:

Alu images were aligned on DAPI by hand using Photoshop 3 (Here no background correction, nor contrast enhancement)

Whole chromosome painting was also performed sequentially,  simultaneously on HSA-13 and HSA-6 and HSA-X:

Karyotyping:

Combining R bands (Alu), G bands (DAPI) and chromosomal painting allows to classify chromosomes in a karyogram:

Left:R Bands (Alu sequences). Right: G bands (Inverse DAPI+DoG filter).