-CMOS Flat-Panel detector characterization and calibration.-Drive Subsystem requirements for X-ray Image Acquisition .-Develop and implement algorithms for Image Quality Assessment in Matlab.-Performance Engineering of algorithms for Real-time Image processing for Multi-Core Processors on CPU using Intel compilers and libraries.

Image Quality Engineer: Development of Medical X-ray equipment - C-Arm. Engineering Image Acquisition, Flat panel detectors, Exposure Management, Image Processing and Image Quality Assessment.Image Processing - GPU Programming - SSE programming - Intel IPP - ImageJ - MatlabQT Programming - libusb interfacing - Wireless Footswitch - Generator Control - LabView

Developed calibration algorithms for CMOS based Flat Panel X-ray detectors.

Development of the following Software Test Protocols for IT3500 Navigation Product- Automatic headset Registration- Automatic fiducial Registration- Surface Registration

AUTOMATIC 3D MEDICAL IMAGE SEGMENTATION AND RIGID REGISTRATIONThe scientific development especially on healthcare is carried out widely by applying the advanced computational techniques to maintain “perfect-ness” in the medical field. Image Registration is widely used in the healthcare domain to study, diagnose, predict and treat the illness of patient. I have made a project study on “Automatic 3D Medical Image Segmentation and Rigid Registration”. In due course of this project I have come up with a new optimization strategy for the registration of medical images. This new optimization method namely Hybrid Genetic Algorithm with Gradient Descent is robust, accurate and computationally efficient compared to either Gradient Descent or the Standard Genetic Algorithm. An automatic headset segmentation algorithm has been developed to aid the registration of the cranial CT/MR images. The algorithms were implemented in C++ using the ITK framework and genetic algorithm library.

Designed and Developed Scanning Optical Microscopy for Raman SpectroscopyThe problem was to develop a low cost Scanning Optical Microscope combined with Raman spectrometer. By using a metallic tip as the Scanning Probe, there is a surface enhancement of the Raman Signal (SERS). Since one needs to collect the Raman signal from the probe tip, the whole setup had to be under a microscope. The motion of the cantilever was detected optically with the help of a Quadrant Photo Detector (QPD). The project includes the developent of mechanical design of the setup, building up of a high voltage power supply to control the piezo cylinders that are used for scanning the sample, interfacing these devices to PC through Analog to Digital and Digital to Analog converers, serial port, using LabView, Matlab and Visual Basic. The Raman Spectrum is recorded using monochromator and CCD. The signal from the QPD had to be processed to achieve better quality. The several stages of noise filters were applied and the signal was enhanced for further analysis. The signal processing steps were developed using Matlab.