Vector Extrapolation and Guided Filtering Methods for Improving Photoacoustic and Microscopic Images

Abstract

Photoacoustic imaging is a noninvasive imaging modality which combines the bene ts of optical contrast and ultrasonic resolution. It is applied widely for monitoring tissue health conditions in the elds of cardiology, ophthalmology, oncology, dermatology, and neurosciences. The photoacoustic tomographic image reconstruction problem is typically ill-posed and requires model-based iterative algorithms. The microscopic image analysis of pathological slides is considered as a gold standard for medical diagnosis. To acquire good quality images, one needs to deploy high-cost microscopes, which becomes prohibitive to have utility low-resource settings. The low-cost microscopic image have low quality due to its inability to acquire focused stack. The thesis deploys methods based on vector extrapolation and guided ltering to improve these photoacoustic and histopathology (microscopic) images. The limited data photoacoustic tomographic image reconstruction problem is known to be ill-posed and hence the iterative reconstruction methods were proven to be effective in terms of providing good quality initial pressure distribution. Often, these iterative methods require a large number of iterations to converge to a solution, in turn making the image reconstruction procedure computationally inefficient. Two variants of vector polynomial extrapolation techniques were proposed to accelerate two standard iterative photoacoustic image reconstruction algorithms, including regularized steepest descent and total variation regularization methods. It was shown using numerical and experimental phantom cases that these extrapolation methods that are proposed in this thesis can provide significant acceleration (as high as 4.7 times) along with added advantage of improving reconstructed image quality. Several algorithms exist to solve the photoacoustic image reconstruction problem depending on the expected reconstructed image features. These reconstruction algorithms promote typically one feature, such as being smooth or sharp, in the out...