RATIONALE AND OBJECTIVES: To evaluate the utility of a convolutional neural network (CNN) with an increased number of contracting and expanding paths of U-net for sparse-view CT reconstruction.
The improvement of the micromachined ultrasound transducer based (CMUT) biosensor fabrication technology and signal processing, which led to higher signal to noise ratio is reported. The biosensor contains interdigitally arranged CMUT structure with ...
Optical coherence tomography angiography (OCTA) is a relatively new imaging modality that generates microvasculature map. Meanwhile, deep learning has been recently attracting considerable attention in image-to-image translation, such as image denois...
Since the advent of deep convolutional neural networks (DNNs), computer vision has seen an extremely rapid progress that has led to huge advances in medical imaging. Every year, many new methods are reported at conferences such as the International C...
Magnetic resonance (MR) images denoising is important in medical image analysis. Denoising methods based on deep learning have shown great promise and outperform all of the other conventional methods. However, deep-learning methods are limited by the...
PURPOSE: Our goal was to use a generative adversarial network (GAN) with feature matching and task-specific perceptual loss to synthesize standard-dose amyloid Positron emission tomography (PET) images of high quality and including accurate pathologi...
The process of denoising of medical images that are corrupted by noise is considered as a long established setback in the signal or image processing domain. An effective system for denoising in order to remove white, salt and also pepper noises by me...
IEEE transactions on bio-medical engineering
Jun 12, 2019
OBJECTIVE: Gastric slow wave abnormalities have been associated with gastric motility disorders. Invasive studies in humans have described normal and abnormal propagation of the slow wave. This study aims to disambiguate the abnormally functioning wa...
PET images often suffer poor signal-to-noise ratio (SNR). Our objective is to improve the SNR of PET images using a deep neural network (DNN) model and MRI images without requiring any higher SNR PET images in training. Our proposed DNN model consist...
Neural networks : the official journal of the International Neural Network Society
May 15, 2019
In this work, a new zeroing neural network (ZNN) using a versatile activation function (VAF) is presented and introduced for solving time-dependent matrix inversion. Unlike existing ZNN models, the proposed ZNN model not only converges to zero within...