Image analysis web application (Python)

[Purpose] the development of the microscope for image analysis Web application

I would like to ask an additional modification and development of the microscope for image analysis single Web application.

There are three broadly divided into.

①, insertion, construction and display of the image

② processing and measurement of image

③ learning function, deep learning function

With respect to ①

bioformats each metadata using (OME-server is not used)

Automatic selection of the Vessel

Automatic string pickled Vessel hole (column, row)

Channel automatic string pickled (overlay display)

Automatic string pickled of the objective lens

Automatic string pickled Z stack

Automatic string pickled timeline

In addition, since there is a case that has been described in the file name, automatic string pickled in string pickled Similarly here also be set in a semi-automatic

Display tiled images with openseadragon, bioformats and with reference to Qupath, because the data is heavy, display it in layers like googleMap

Tile to be displayed must be consolidated, implementation of Stichng functions and paste recognize the pattern of the ladder of image

Combination of tile connection order Vertical / horizontal / horizontal / horizontal / vertical / vertical / cow descending order, spiral (2nd sheet requires vertical / horizontal selection)

Setting the number of rows and columns for the number of sheets

Set of XY of the gap

Setting the overlap pixel region of the% set-XY pattern matching pattern matching

Shading correction

White balance Black balance setting

Edge adsorption

Combined without adsorption set

3D display and extraction

Display and extraction of the time line

Maintenance of the bit number

bioformats download page

[login to view URL]

To see also [login to view URL] for python bridge of bioformats

②, with respect to the ③

2D and 3D file item of implementation: openCV, openGL, accompanying github

(Refer to the functioniist tab for binarization, emphasis, averaging, 2D / 3D deconvolution, simple deconvolution, digital differential interference contrast, digital phase contrast, focus composition, separation, homogenization, subtraction, calculation, etc.)

Acquisition of implementation and measurement data of the measurement

Implementation of machine learning function

Implementation of deep learning function

About 1 implementation of deep learning function library (see Aplication tab)

Functionally string pickled image is OMEO, CellProfiler, image filter processing and analysis and machine learning ImagePro10, Imjoy, deep learning is here and requested if you could imagine the TensorFlow (such as free public library of breast cancer Ki67) It is something that is I think I can understand.

In addition to Ki67, the library is implemented with data on Her2, HE, comet assay, drug efficacy, cell cycle, cytotoxicity, wafer inspection, winding, colocarization, and cell localization.

Plus I attach the documentation because it is more professional with respect to implementation and construction of the image.

Excel priority of the file of the O column SS and S, and will be content that A is to ask this time.

Link of explanatory material: [login to view URL]

Link destination of data created halfway: [login to view URL]

It will be in specialized areas you need variety investigate on your own.

After check attachments carefully, please apply from trying to advance, especially for bioformats.

Start your proposal with "Bioformats".

Also let me know your experiences and your weekly or monthly rate.

Regards

Python Image Processing Machine Learning (ML) Vue.js OpenCV

ID do Projeto: #28950102

Sobre o projeto