Projection-to-image transform frame: a lightweight block reconstruction network for computed tomography
G Ma, X Zhao, Y Zhu, H Zhang - Physics in Medicine & Biology, 2022 - iopscience.iop.org
Several reconstruction networks have been invented to solve the problem of learning-based
computed tomography (CT) reconstruction. However, the application of neural networks to …
computed tomography (CT) reconstruction. However, the application of neural networks to …
Accessible, affordable and low-risk lungs health monitoring in covid-19: Deep cascade reconstruction from degraded lr-uldct
We present deep cascade reconstruction of degraded low-resolution ultra-low-dose
computed tomography (LR-ULDCT) chest images to restored and super-resolved (SR) …
computed tomography (LR-ULDCT) chest images to restored and super-resolved (SR) …
Residual Feature Attentional Fusion Network for Lightweight Chest CT Image Super-Resolution.
K Yang, L Zhao, X Wang, M Zhang… - Computers …, 2023 - search.ebscohost.com
The diagnosis of COVID-19 requires chest computed tomography (CT). High-resolution CT
images can provide more diagnostic information to help doctors better diagnose the …
images can provide more diagnostic information to help doctors better diagnose the …
3d u-netr: Low dose computed tomography reconstruction via deep learning and 3 dimensional convolutions
In this paper, we introduced a novel deep learning-based reconstruction technique for low-
dose CT imaging using 3 dimensional convolutions to include the sagittal information unlike …
dose CT imaging using 3 dimensional convolutions to include the sagittal information unlike …
Interactive smoothing parameter optimization in dbt reconstruction using deep learning
Medical image reconstruction algorithms such as Penalized Weighted Least Squares
(PWLS) typically rely on a good choice of tuning parameters such as the number of …
(PWLS) typically rely on a good choice of tuning parameters such as the number of …
Deep Learning Algorithm for COVID‐19 Classification Using Chest X‐Ray Images
S VJ - Computational and Mathematical Methods in Medicine, 2021 - Wiley Online Library
Early diagnosis of the harmful severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐
2), along with clinical expertise, allows governments to break the transition chain and flatten …
2), along with clinical expertise, allows governments to break the transition chain and flatten …
[HTML][HTML] Covid-19 identification from low-quality computed tomography using a modified enhanced super-resolution generative adversarial network plus and siamese …
Computed Tomography has become a vital screening method for the detection of
coronavirus 2019 (COVID-19). With the high mortality rate and overload for domain experts …
coronavirus 2019 (COVID-19). With the high mortality rate and overload for domain experts …
CT iterative vs deep learning reconstruction: comparison of noise and sharpness
Objectives To compare image noise and sharpness of vessels, liver, and muscle in lower
extremity CT angiography between “adaptive statistical iterative reconstruction-V”(ASIR-V) …
extremity CT angiography between “adaptive statistical iterative reconstruction-V”(ASIR-V) …
Research and Application of Deep Learning in Medical Image Reconstruction and Enhancement
In recent years, deep learning technology has made remarkable progress in medical image
reconstruction and enhancement, and has become one of the research hotspots in the field …
reconstruction and enhancement, and has become one of the research hotspots in the field …
Enhancing low quality in radiograph datasets using wavelet transform convolutional neural network and generative adversarial network for COVID-19 identification
GU Nneji, J Cai, D Jianhua… - 2021 4th …, 2021 - ieeexplore.ieee.org
The coronavirus disease of 2019 (COVID-19) pandemic has caused a global public health
epidemic since there is no 100% vaccine to cure or prevent the further spread of the virus …
epidemic since there is no 100% vaccine to cure or prevent the further spread of the virus …