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 https://www.openmicroscopy.org/bio-formats/ To see also image.sc.forum 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:
Link destination of data created halfway: https://drive.google.com/drive/folders/18UrqF7xMjv3PfnQxW7mnMuNuqsueeSSN?usp=sharing
[The proposed method]
It will be in specialized areas you need variety investigate on your own. Please apply from trying to advance, especially for bioformats. [Point to emphasize] Quality, delivery time, the proposed force, response, who has contracted the NDA. Person who can Yaritoge to the end that the request was The information is all that is described here and the information in the attached file. I don't have any more information so no meetings are needed.
Please note that safe pay will not occur. ... Show more