PURPOSE: To evaluate the feasibility and utility of a deep learning (DL)-based reconstruction for improving the SNR of hyperpolarized Xe lung ventilation MRI.
OBJECTIVES: Holistic segmentation of CT structural alterations with 3D deep learning has recently been described in cystic fibrosis (CF), allowing the measurement of normalized volumes of airway abnormalities (NOVAA-CT) as an automated quantitative o...
BACKGROUND: Recent advancements in anomaly detection have paved the way for novel radiological reading assistance tools that support the identification of findings, aimed at saving time. The clinical adoption of such applications requires a low rate ...
Fluorescence intravital microscopy captures large data sets of dynamic multicellular interactions within various organs such as the lungs, liver, and brain of living subjects. In medical imaging, edge detection is used to accurately identify and deli...
IEEE/ACM transactions on computational biology and bioinformatics
Aug 9, 2024
In this paper, a CNN-MLP model (CMM) is proposed for COVID-19 lesion segmentation and severity grading in CT images. The CMM starts by lung segmentation using UNet, and then segmenting the lesion from the lung region using a multi-scale deep supervis...
IEEE/ACM transactions on computational biology and bioinformatics
Aug 8, 2024
Current human being's lifestyle has caused / exacerbated many diseases. One of these diseases is cancer, and among all kinds of cancers like, brain pulmonary; lung cancer is fatal. The cancers could be detected early to save lives using Computer Aide...
IEEE/ACM transactions on computational biology and bioinformatics
Aug 8, 2024
Pneumonia mainly refers to lung infections caused by pathogens, such as bacteria and viruses. Currently, deep learning methods have been applied to identify pneumonia. However, the traditional deep learning methods for pneumonia identification take l...
IEEE/ACM transactions on computational biology and bioinformatics
Aug 8, 2024
Currently, Coronavirus Disease 2019 (COVID-19) is still endangering world health and safety and deep learning (DL) is expected to be the most powerful method for efficient detection of COVID-19. However, patients' privacy concerns prohibit data shari...
Journal of computer assisted tomography
Aug 2, 2024
OBJECTIVE: The purpose of this study is to explore the impact of deep learning image reconstruction (DLIR) algorithm on the quantification of radiomic features in ultra-low-dose computed tomography (ULD-CT) compared with adaptive statistical iterativ...