Browsing by Advisor "Yalavarthy, Phaneendra K"
Now showing items 1-16 of 16
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Accelerating Estimation of Perfusion Maps in Contrast X-ray Computed Tomography using Many-core CPUs and GPUs
X-ray Computed Tomography (CT) perfusion imaging is a non-invasive medical imaging modality that has been established as a fast and economical method for diagnosing cerebrovascular diseases such as acute ischemia, sub-arachnoid ... -
Automated Selection of Hyper-Parameters in Diffuse Optical Tomographic Image Reconstruction
(2018-03-16)Diffuse optical tomography is a promising imaging modality that provides functional information of the soft biological tissues, with prime imaging applications including breast and brain tissue in-vivo. This modality uses ... -
Development and Validation of Analytical Models for Diffuse Fluorescence Spectroscopy/Imaging in Regular Geometries
(2018-03-15)New advances in computational modeling and instrumentation in the past decade has enabled the use of electromagnetic radiation for non-invasive monitoring of the physio-logical state of biological tissues. The near infrared ... -
Development of advanced regularization methods to improve photoacoustic tomography
Photoacoustic tomography (PAT) is a scalable imaging modality having huge potential for imaging biological samples at very high depth to resolution ratio, thereby playing pivotal role in the areas of neuroscience, ... -
Development of Efficient Computational Methods for Better Estimation of Optical Properties in Diffuse Optical Tomography
(2018-04-02)Diffuse optical tomography (DOT) is one of the promising imaging modalities that pro- vides functional information of the soft biological tissues in-vivo, such as breast and brain tissues. The near infrared (NIR) light ... -
Development of Fully Data Driven Novel Methods for Improving the micro-Computed Tomography Image Quality for Digital Rock
The Digital Rock workflow is an emerging framework utilizing advances in imaging technologies and state-of-the-art image processing algorithms to construct digital models of reservoir rocks. These digital models become ... -
Development of Next Generation Image Reconstruction Algorithms for Diffuse Optical and Photoacoustic Tomography
(2018-02-15)Biomedical optical imaging is capable of providing functional information of the soft bi-ological tissues, whose applications include imaging large tissues, such breastand brain in-vivo. Biomedical optical imaging uses ... -
Development of Novel Deep Learning Methods for Fast-MRI: Anatomical Image Reconstruction to Quantitative Imaging
In medical imaging, the task of estimating interpretable anatomical images from raw scanner data - based on underlying physical principles - is known as an "inverse problem". The solution to such inverse problems can be ... -
Development of Novel Deep Learning Models with Improved Generalizability for Medical Image Analysis
Medical imaging is a process of visualization of disease/tissue in a non-invasive manner. Several imaging techniques like computed tomography (CT), magnetic resonance imaging (MRI), optical coherence tomography (OCT), and ... -
Development of Novel Reconstruction Methods Based on l1--Minimization for Near Infrared Diffuse Optical Tomography
(2018-03-03)Diffuse optical tomography uses near infrared (NIR) light as the probing media to recover the distributions of tissue optical properties. It has a potential to become an adjunct imaging modality for breast and brain imaging, ... -
Development of Sparse Recovery Based Optimized Diffuse Optical and Photoacoustic Image Reconstruction Methods
(2018-01-11)Diffuse optical tomography uses near infrared (NIR) light as the probing media to re-cover the distributions of tissue optical properties with an ability to provide functional information of the tissue under investigation. ... -
Improving photoacoustic imaging with model compensating and deep learning methods
Photoacoustic imaging is a hybrid biomedical imaging technique combining optical ab- sorption contrast with ultrasonic resolution. It is a non-invasive technique that is scalable to reveal structural, functional, and ... -
Novel Deep Learning Methods for Improving Low-Dose Computed Tomography Perfusion Imaging of Brain
Computed Tomography (CT) Perfusion imaging is a non-invasive medical imaging modality that has also established itself as a fast and economical imaging modality for diagnosing cerebrovascular diseases such as acute ischemia, ... -
Toward Computationally Efficient Models for Near-infrared and Photoacoustic Tomographic Imaging
(2017-11-28)Near Infrared (NIR) and Photoacoustic (PA) Imaging are promising imaging modalities that provides functional information of the soft biological tissues in-vivo, with applica-tions in breast and brain tissue imaging. These ... -
Unsupervised Test-time Adaptation for Patient-Specific Deep Learning Models in Medical Imaging
Deep learning (DL) models have achieved state-of-the-art results in multiple medical imaging applications, resulting in the widespread adoption of artificial intelligence (AI) models for radiological workflows. Despite ... -
Vector Extrapolation and Guided Filtering Methods for Improving Photoacoustic and Microscopic Images
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, ...