PURPOSE: Data completion is commonly employed in dual-source, dual-energy computed tomography (CT) when physical or hardware constraints limit the field of view (FoV) covered by one of two imaging chains. Practically, dual-energy data completion is a...
PURPOSE: To characterize the noise and spatial resolution properties of a commercially available deep learning-based computed tomography (CT) reconstruction algorithm.
In this paper we present a generalized Deep Learning-based approach for solving ill-posed large-scale inverse problems occuring in medical image reconstruction. Recently, Deep Learning methods using iterative neural networks (NNs) and cascaded NNs ha...
The use of image covariates to build a classification model has lots of impact in various fields, such as computer science, medicine, and so on. The aim of this paper is to develop an estimation method for logistic regression model with image covaria...
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Jun 15, 2020
We study training deep neural network (DNN) frequency-domain beamformers using simulated and phantom anechoic cysts and compare to training with simulated point target responses. Using simulation, physical phantom, and in vivo scans, we find that tra...
Journal of applied clinical medical physics
Jun 15, 2020
BACKGROUND: A proton therapy system with 190° gantries uses robotic couch rotations to change the treatment beam laterality. Couch rotations are typically validated clinically with post-rotation radiographic imaging.
Biomedical physics & engineering express
Jun 12, 2020
The use of intra-operative imaging system as an intervention solution to provide more accurate localization of complicated structures has become a necessity during the neurosurgery. However, due to the limitations of conventional imaging systems, hig...
Computational and mathematical methods in medicine
Jun 11, 2020
This paper proposes a deep learning method based on electrical impedance tomography (EIT) to estimate the thickness of abdominal subcutaneous fat. EIT for evaluating the thickness of abdominal subcutaneous fat is an absolute imaging problem that aims...
International journal of computer assisted radiology and surgery
Jun 3, 2020
PURPOSE: We investigate the feasibility of reconstructing ultrasound images directly from raw channel data using a deep learning network. Starting from the raw data, we present the network the full measurement information, allowing for a more generic...
International journal of computer assisted radiology and surgery
May 22, 2020
PURPOSE: The manual generation of training data for the semantic segmentation of medical images using deep neural networks is a time-consuming and error-prone task. In this paper, we investigate the effect of different levels of realism on the traini...
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