Doctor of Engineering (Dr.-Ing/PhD)
Technical University of Munich (TUM) and Helmholtz Zentrüm Muenchen, Germany
TUM Graduate School of Bioengineering
Thesis : Visual Quality Enhancement in Multispectral Optoacoustic Tomography (2018) [eBook]
Multi-Spectral Optoacoustic Tomography (MSOT) is capable of high resolution 3D visualization of molecular probes located deep in scattering living tissues. This method can simultaneously deliver anatomical, functional and molecular information with both high resolution and penetration capabilities. In order to accurately recover maps of local optical absorbance using MSOT, multiple parameters related to both light and ultrasound propagation characteristics of the medium need to be adequately selected. We have investigated algorithms for automatic speed-of-sound calibration in cross-sectional optoacoustic tomography, and developed efficient hybrid focusing metrics to enhance the focusing performance. Further, we employed multi-resolution and scale- space based signal processing techniques for optoacoustic image segmentation, which is subsequently used to improve accuracy of the image reconstruction routines. To improve the image resolution, we applied geometric pixel super-resolution methods that integrates information from multiple optoacoustic images acquired at sub-diffraction steps into one high resolution image by means of an iterative registration algorithm. The developed algorithms address the common goal of improving image quality of optoacoustic images, using computer vision and image analysis techniques. To validate the methods, extensive experimental has been performed on target phantoms, as well as on ex-vivo and in-vivo tissue samples. We have successfully demonstrated significant improvements in terms of optoacoustic image resolution and quality without introducing major alterations into the signal acquisition hardware or inversion algorithms.
MS by Research
Indian Institute of Technology Kharagpur, INDIA
Thesis : Application of Multiresolution Signal Processing to Acoustical Cardiac Signals (2011) [Thesis]
Study of the disease demographics in human population indicates that cardiac ailments are the primary cause of premature death and it is pervasive nearly in all communities. A need for emergent technologies is thus felt to address the rising trend of cardiac conditions at the grassroot levels. The dissertation proposes an improved framework for a point-of-care device to analyze of acoustic cardiac signals towards auscultatory heart sound based cardiac screening. Historically, the development of an automated heart sound analysis system has been slow because of the lack of well-defined gold standards in nomenclature, recording transducers, recording location and the inherent complexity associated with interpretation, specially in noisy environments of out-patient departments and primary healthcare centers. The proposed framework aims to address these issues and has evolved through continual feedback from cardiologists, thus embedding medical acumen with signal processing techniques. The designed system employs multi-resolution signal processing techniques to denoise acoustic cardiac signals, resulting in clearer and more accurate representation and visualization to make clinical interpretation easier. This dissertation also compares different signal denoising methods based on embedded platforms, and modifies existing techniques for best wavelet basis functions. Nonetheless, it incorporates a nationwide survey based investigatory report entitled. ‘Practice of cardiac auscultation for determination of its effectiveness in Diagnosis,’ to achieve better validation of clinical inputs used in this study and for further improvements of the system.
B.E. in Biomedical Engineering
Manipal Institute of Technology, Manipal University, INDIA
Thesis : Development of Cardiac Diagnosis & Sustainable Healthcare Delivery System for Rural India (2007) [Poster]