Sometimes your needs do not match an out-of-the-box solution and business goes on as usual. Optra helps clients solve the challenges they face when identifying gaps in their applications, with Custom Algorithm Development Services. Optra’s team of algorithm development experts gets started with an in-depth analysis of a client’s requirements to make an appropriate planned strategy for the tool’s performance and machine-learning functionality. Optra will improve any user interfaces, test all development and modifications, and fix any bugs and amend product features according to test results.


Examples of Optra client’s custom algorithm development:

  1. Imaging Cytometry (DNA Ploidy) Recognition Algorithms
  2. Feature Extraction Algorithm for DNA Microarray
  3. Retinopathy of Prematurity (ROP) digital slide analysis solution
  4. Algorithms for identification and quantification of stained and non-stained epithelial cells for IHC-based ER, PR and Ki67 nuclear markers


Imaging-based DNA Ploidy is a quantitation of nuclear DNA content by cytometry to predict the tumor's aggressiveness.

After DNA-staining, the nuclear IOD (Integrated Optical Density) is quantitated, which is the cytometric equivalent of its DNA content. Ploidy analysis using image analysis provides more reliable ploidy results due to direct visualization and selection of cancer cells.

Algorithm functionalities include:

  • Identification of tumor and reference cells based on morphological characteristics
  • Quantization of number of tumor and reference cells to define adequacy of the test sample
  • Quantization of optical density of reference as well tumor cells
  • Quantization of integrated optical density of reference as well tumor cells
  • Exporting results as
    • Number of reference cells
    • Number of tumor cells
    • IOD values of each reference cell as XML
    • IOD values of each tumor cell as XML
    • Mean IOD for tumor cells
    • Mean IOD for reference cells
  • Using these values, plotting histogram for further statistical analysis

Algorithm functionalities include:

  • Identification of DNA spots in the microarray image
  • Gridding of the microarray; unique for honey comb structure
  • Spot Indexing, locating the spot centers with the help of bounding boxes, and verification using XML file
  • Calculating the feature values for each sub-array
  • Exporting results as output XML – containing feature values for each sub-array

Software solution to annotate and analyze neovascular vessels from an eye disease model (Retinopathy of Prematurity).

Algorithm functionalities include:

  1. Identification of neovascular vessels (region of interest)
  2. Quantification of nuclei within region of interest (analysis)
  3. Reporting of quantification results (reporting)

Software solution to annotate and analyze neovascular vessels from an eye disease model (Retinopathy of Prematurity).

Algorithm functionalities include:

  • Image Quality module
  • Analysis module
  • Report generation module

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