Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1097/DSS.0000000000001953 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Deep Convolutional Neural Networks on Multiclass Classification of Three-Dimensional Brain Images for Parkinson's Disease Stage Prediction.
J Imaging Inform Med
January 2025
Department of Anesthesiology, E-Da Cancer Hospital, I-Shou University, Kaohsiung, Taiwan.
Parkinson's disease (PD), a degenerative disorder of the central nervous system, is commonly diagnosed using functional medical imaging techniques such as single-photon emission computed tomography (SPECT). In this study, we utilized two SPECT data sets (n = 634 and n = 202) from different hospitals to develop a model capable of accurately predicting PD stages, a multiclass classification task. We used the entire three-dimensional (3D) brain images as input and experimented with various model architectures.
View Article and Find Full Text PDFUnlocking the Power of 3D Convolutional Neural Networks for COVID-19 Detection: A Comprehensive Review.
J Imaging Inform Med
January 2025
College of Science and Engineering, Hamad Bin Khalifa University, Ar-Rayyan, Qatar.
The advent of three-dimensional convolutional neural networks (3D CNNs) has revolutionized the detection and analysis of COVID-19 cases. As imaging technologies have advanced, 3D CNNs have emerged as a powerful tool for segmenting and classifying COVID-19 in medical images. These networks have demonstrated both high accuracy and rapid detection capabilities, making them crucial for effective COVID-19 diagnostics.
View Article and Find Full Text PDFEffect of a Training System Utilizing 3D-Printed Patient-Specific Vascular Models on Endovascular Catheterization Performance.
J Vasc Interv Radiol
January 2025
Department of Diagnostic Imaging, Faculty of Medicine, Hokkaido University, N-15, W-7, Kita-ku, Sapporo, Hokkaido 060-8638, Japan; Global Center for Biomedical Science and Engineering, Faculty of Medicine, Hokkaido University, N-14, W-5, Kita-ku, Sapporo, Hokkaido 060-8648, Japan.
This study aimed to examine the effect of simulation training using a three-dimensional (3D)-printed patient-specific vascular model on the advanced vascular catheterization skills of experienced interventional radiologists (IRs). Two specific anatomic types of 3D-printed patient-specific models from two patients with challenging celiac axis arterial anatomy were constructed. The Global Rating Scale of Endovascular Performance (GRS-EP) was used to evaluate vascular insertion skills.
View Article and Find Full Text PDFHigh-Throughput Chemotherapeutic Drug Screening System for Gastric Cancer (Cure-GA).
Ann Surg Oncol
January 2025
Department of Surgery, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
Background: Three dimensional (3D) cell cultures can be effectively used for drug discovery and development but there are still challenges in their general application to high-throughput screening. In this study, we developed a novel high-throughput chemotherapeutic 3D drug screening system for gastric cancer, named 'Cure-GA', to discover clinically applicable anticancer drugs and predict therapeutic responses.
Methods: Primary cancer cells were isolated from 143 fresh surgical specimens by enzymatic treatment.
A 3D decoupling Alzheimer's disease prediction network based on structural MRI.
Health Inf Sci Syst
December 2025
School of Mathematics and Computing, University of Southern Queensland, 487-535 West Street, Toowoomba, QLD 4350 Australia.
Purpose: This paper aims to develop a three-dimensional (3D) Alzheimer's disease (AD) prediction method, thereby bettering current predictive methods, which struggle to fully harness the potential of structural magnetic resonance imaging (sMRI) data.
Methods: Traditional convolutional neural networks encounter pressing difficulties in accurately focusing on the AD lesion structure. To address this issue, a 3D decoupling, self-attention network for AD prediction is proposed.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!