Radiology

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Acquisition-Independent Deep Learning for Quantitative MRI Parameter Estimation using Neural Controlled Differential Equations

Deep learning has proven to be a suitable alternative to least-squares (LSQ) fitting for parameter...

Diagnostic Performance of Deep Learning Applications in Hepatocellular Carcinoma Detection Using Computed Tomography Imaging.

Hepatocellular carcinoma (HCC) is a prevalent cancer that significantly contributes to mortality glo...

Dec 2024 39760649
Conformal Risk Control for Pulmonary Nodule Detection

Quantitative tools are increasingly appealing for decision support in healthcare, driven by the gr...

A Review on the Integration of Artificial Intelligence and Medical Imaging in IVF Ovarian Stimulation

Artificial intelligence (AI) has emerged as a powerful tool to enhance decision-making and optimiz...

MRI Reconstruction with Regularized 3D Diffusion Model (R3DM)

Magnetic Resonance Imaging (MRI) is a powerful imaging technique widely used for visualizing struc...

[Coronary artery segmentation based on Transformer and convolutional neural networks dual parallel branch encoder neural network].

Manual segmentation of coronary arteries in computed tomography angiography (CTA) images is ineffici...

Dec 2024 40000209
[Cardiac magnetic resonance image segmentation based on lightweight network and knowledge distillation strategy].

To address the issue of a large number of network parameters and substantial floating-point operatio...

Dec 2024 40000210
A Review of Latent Representation Models in Neuroimaging

Neuroimaging data, particularly from techniques like MRI or PET, offer rich but complex informatio...

Pruning Unrolled Networks (PUN) at Initialization for MRI Reconstruction Improves Generalization

Deep learning methods are highly effective for many image reconstruction tasks. However, the perfo...

Resolution-Robust 3D MRI Reconstruction with 2D Diffusion Priors: Diverse-Resolution Training Outperforms Interpolation

Deep learning-based 3D imaging, in particular magnetic resonance imaging (MRI), is challenging bec...

Analysis of Transferred Pre-Trained Deep Convolution Neural Networks in Breast Masses Recognition

Breast cancer detection based on pre-trained convolution neural network (CNN) has gained much inte...

Enhancing Reconstruction-Based Out-of-Distribution Detection in Brain MRI with Model and Metric Ensembles

Out-of-distribution (OOD) detection is crucial for safely deploying automated medical image analys...

FFA Sora, video generation as fundus fluorescein angiography simulator

Fundus fluorescein angiography (FFA) is critical for diagnosing retinal vascular diseases, but beg...

PINN-EMFNet: PINN-based and Enhanced Multi-Scale Feature Fusion Network for Breast Ultrasound Images Segmentation

With the rapid development of deep learning and computer vision technologies, medical image segmen...

Multi-atlas Ensemble Graph Neural Network Model For Major Depressive Disorder Detection Using Functional MRI Data

Major depressive disorder (MDD) is one of the most common mental disorders, with significant impac...

VerSe: Integrating Multiple Queries as Prompts for Versatile Cardiac MRI Segmentation

Despite the advances in learning-based image segmentation approach, the accurate segmentation of c...

Label-Efficient Data Augmentation with Video Diffusion Models for Guidewire Segmentation in Cardiac Fluoroscopy

The accurate segmentation of guidewires in interventional cardiac fluoroscopy videos is crucial fo...

MiniGPT-Pancreas: Multimodal Large Language Model for Pancreas Cancer Classification and Detection

Problem: Pancreas radiological imaging is challenging due to the small size, blurred boundaries, a...

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