[HTML][HTML] Nerve optic segmentation in CT images using a deep learning model and a texture descriptor

R Ranjbarzadeh, S Dorosti… - Complex & Intelligent …, 2022 - Springer
The increased intracranial pressure (ICP) can be described as an increase in pressure
around the brain and can lead to serious health problems. The assessment of ultrasound …

[HTML][HTML] Protecting digital images using keys enhanced by 2D chaotic logistic maps

M Abu-Faraj, A Al-Hyari, C Obimbo, K Aldebei… - Cryptography, 2023 - mdpi.com
This research paper presents a novel digital color image encryption approach that ensures
high-level security while remaining simple and efficient. The proposed method utilizes a …

[HTML][HTML] DeepPN: a deep parallel neural network based on convolutional neural network and graph convolutional network for predicting RNA-protein binding sites

J Zhang, B Liu, Z Wang, K Lehnert, M Gahegan - BMC bioinformatics, 2022 - Springer
Background Addressing the laborious nature of traditional biological experiments by using
an efficient computational approach to analyze RNA-binding proteins (RBPs) binding sites …

Virtual differential phase‐contrast and dark‐field imaging of x‐ray absorption images via deep learning

X Ge, P Yang, Z Wu, C Luo, P Jin… - Bioengineering & …, 2023 - Wiley Online Library
Weak absorption contrast in biological tissues has hindered x‐ray computed tomography
from accessing biological structures. Recently, grating‐based imaging has emerged as a …

A novel multivariable time series prediction model for acute kidney injury in general hospitalization

J Xu, Y Hu, H Liu, W Mi, G Li, J Guo, Y Feng - International Journal of …, 2022 - Elsevier
Objective Early recognition and prevention are important to reduce the risk of acute kidney
injury (AKI). We aimed to build a novel multivariate time series prediction model for dynamic …

Deep-learning-based denoising of X-ray differential phase and dark-field images

K Ren, Y Gu, M Luo, H Chen, Z Wang - European Journal of Radiology, 2023 - Elsevier
Purpose Statistical photon noise has always been a common problem in X-ray multi-contrast
imaging and significantly influenced the quality of retrieved differential phase and dark-field …

DeepPhase: learning phase contrast signal from dual energy X-ray absorption images

R Luo, Y Ge, Z Hu, D Liang, ZC Li - Displays, 2021 - Elsevier
Due to the high hardware complexity and low dose efficiency of existing X-ray phase
contrast imaging, the biomedical and clinical applications of this novel imaging technique …

Imaging of conductivity distribution based on a combined reconstruction method in brain electrical impedance tomography.

Y Shi, Y Lou, M Wang, S Zheng… - Inverse Problems & …, 2023 - search.ebscohost.com
Electrical impedance tomography (EIT) is a promising technique in medical imaging. With
this technique, pathology-related conductivity variation can be visualized. Nevertheless …

INSIDEnet: Interpretable nonexpansive data‐efficient network for denoising in grating interferometry breast CT

S van Gogh, Z Wang, M Rawlik, C Etmann… - Medical …, 2022 - Wiley Online Library
Purpose Breast cancer is the most common malignancy in women. Unfortunately, current
breast imaging techniques all suffer from certain limitations: they are either not fully three …

Investigating the impact of novel XRayGAN in feature extraction for thoracic disease detection in chest radiographs: lung cancer

T Awan, KB Khan - Signal, Image and Video Processing, 2024 - Springer
Lung cancer remains one of the most lethal malignancies worldwide, underscoring the
urgent need for early detection and intervention to improve survival rates. While computed …