THE OBJECTIVE: This study aims to propose a new model to predict the specific treatment effectiveness at site level by analyzing massive amounts of periodontal clinical data with deep learning methods.
The identification of abnormal findings manifested in retinal fundus images and diagnosis of ophthalmic diseases are essential to the management of potentially vision-threatening eye conditions. Recently, deep learning-based computer-aided diagnosis ...
The quality of red blood cells (RBCs) in stored blood has a direct impact on the recovery of patients treated by blood transfusion, which directly reflects the quality of blood. The traditional means for blood quality evaluation involve the use of re...
The progressive loss of motor function in the brain is a hallmark of Parkinson's disease (PD). Electroencephalogram (EEG) signals are commonly used for early diagnosis since they are associated with a brain disorder. This work aims to find a better w...
Hepatobiliary & pancreatic diseases international : HBPD INT
Apr 11, 2023
BACKGROUND: Gallbladder carcinoma (GBC) is highly malignant, and its early diagnosis remains difficult. This study aimed to develop a deep learning model based on contrast-enhanced computed tomography (CT) images to assist radiologists in identifying...
Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Apr 11, 2023
To evaluate the effects of deep learning reconstruction (DLR) on image quality of abdominal computed tomography (CT) in patients without arm elevation compared with hybrid-iterative reconstruction (Hybrid-IR) and filtered back projection (FBP). In ...
OBJECTIVES: The aim of the study is to develop and evaluate the performance of a deep learning (DL) model to triage breast magnetic resonance imaging (MRI) findings in high-risk patients without missing any cancers.
BACKGROUND: Photon-counting-detector CT (PCD-CT) enables the production of virtual monoenergetic images (VMIs) at a high spatial resolution (HR) via simultaneous acquisition of multi-energy data. However, noise levels in these HR VMIs are markedly in...
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 images. We intend to develop a deep learning-based denoising al...
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