Development of microscope for image analysis Web application I would like to request additional modification and development of a microscope for image analysis, but it is a single web application. There are three main types. ①, image insertion, construction, display ② image processing and measurement ③ learning function, deep learning function ① are bioformatted using each metadata (OME server is not used). Column, row) Channel automatic string pickles (overlay display) Objective lens automatic string pickles Automatic string pickles Z stack automatic string pickles Timeline Also, because it may be listed in the file name, automatic string pickles Like the string, it is set semi-automatically here as well. Use openseadragon, bioformats and refer to the Qupath to display the tile image. Since the data is heavy, it will be displayed in a layer like googleMap. Consolidate the tiles you want to display and implement and paste the Stichng function. Recognize the image ladder pattern Combination of tile connection order Vertical / horizontal / horizontal / horizontal / vertical / vertical / cow descending order, spiral (2nd sheet requires vertical / horizontal selection) Number of rows and columns Set XY set of setting gap Set% set overlap pixel area-XY pattern matching pattern matching Shading correction White balance Black balance setting Edge adsorption No adsorption combination 3D display and extraction Timeline display and maintenance of extraction bit number bioformats download page [login to view URL] See also [login to view URL] for python bridge of bioformats ②, ③ Regarding 2D and 3D file items of implementation: openCV, openGL, accompanying github (binarization, emphasis) , Averaging, 2D / 3D deconvolution, simple deconvolution, see functioniist tab), Digital Differential Interference Contrast, Digital Phase Contrast, Focus Configuration, Separation, Homogenization, Subtraction, Calculation, etc.) Implementation and Acquisition of measurement data Measurement a Implementation of machine learning function Implementation of deep learning function Approximately one implementation of the deep learning function library (see [Application] tab) The images with functionally selected character strings are OMEO, CellProfiler, and images. Filter processing and analysis, machine learning ImagePro10, Imjoy, deep learning. Imagine TensorFlow (such as the free public library for breast cancer Ki67) and you'll understand. In addition to Ki67, the library contains data on Her2, HE, comet assay, efficacy, cell cycle, cytotoxicity, wafer testing, windings, coloculation, and cell localization. In addition, you need more specialized skills in implementing and building images.
Explanatory material link:
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Link destination of data created on the way: https: //[login to view URL] usp = Sharing
Current data changed from the middle.
Please tell me your github id for private github
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It will be a discipline where you need to investigate diversity on your own. Especially for bioformats, apply by trying to move forward. [Emphasis] Quality, delivery date, proposed power, and response to NDA contracts. A person who can carry out to the end of the request. Only the information and attachment information is listed here.
No further information is available, so no meetings are needed.