Medical Image and Signal processing ML for SpecificDiagnosti

Medical Image and Signal Processing Libraries: Tensorflow, Keras, Scipy, Sklearn, OpenCV, Pillow, CUDA, cudNN,SQL, Pandas, matplotlib Stack: - Deep knowledge in biomedical engineering- Analytical method and statistical analysis of medical image/signals. - Machine learning for image analysis (CNN/DNN) - SQL as well as NoSQL database technologies Key Skill: - Computer Vision (Object Recognition) - Medical image analysis - Large-scale image processing - 2d-filtering - Quality Analysis Pipeline Objective: Use cutting-edge computer vision and machine learning approach (tools and algorithms) to develop a powerful, low-cost, novel technology that combines the identification of bacterial infection with the determination of the most effective antibiotic to treat it, enabling results that currently take days in just life-saving hours. Image(the sensor data) processing and analysis algorithm development are at the core of this job and the key tasks that were required to contribute are: Accomplishments: - Developed and implemented image processing algorithms to convert raw sensor signals into colorimetric time series data with the highest signal integrity. - Developed and implemented vision-based quality control tools to be deployed at manufacturing (built and deployed the custom object detection CNN model). - Developed tools to analyze and visualize high-volume, high-dimensional data to find interesting trends and correlations. - Maintained image processing and data analysis software stack. - Developed analytical methods and statistical analysis for processing high-volume, temporal high-dimensional data streams generated in real-time from proprietary sensor technology. - Developed an algorithm for decisions and measurements of multi-dimensional data streams. - Provided proper documentation of analyzed results.