Radiology

Nuclear Medicine

Latest AI and machine learning research in nuclear medicine for healthcare professionals.

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A multi-view prognostic model for diffuse large B-cell lymphoma based on kernel canonical correlation analysis and support vector machine.

BACKGROUND AND OBJECTIVE: Positron emission tomography/computed tomography (PET/CT) is recommended a...

Self-supervised neural network for Patlak-based parametric imaging in dynamic [F]FDG total-body PET.

PURPOSE: The objective of this study is to generate reliable K parametric images from a shortened [F...

3D full-dose brain-PET volume recovery from low-dose data through deep learning: quantitative assessment and clinical evaluation.

OBJECTIVES: Low-dose (LD) PET imaging would lead to reduced image quality and diagnostic efficacy. W...

Enhancement and evaluation for deep learning-based classification of volumetric neuroimaging with 3D-to-2D knowledge distillation.

The application of deep learning techniques for the analysis of neuroimaging has been increasing rec...

F-FDG PET/CT-based habitat radiomics combining stacking ensemble learning for predicting prognosis in hepatocellular carcinoma: a multi-center study.

BACKGROUND: This study aims to develop habitat radiomic models to predict overall survival (OS) for ...

A deep learning method for the recovery of standard-dose imaging quality from ultra-low-dose PET on wavelet domain.

PURPOSE: Recent development in positron emission tomography (PET) dramatically increased the effecti...

Multi-scale multimodal deep learning framework for Alzheimer's disease diagnosis.

Multimodal neuroimaging data, including magnetic resonance imaging (MRI) and positron emission tomog...

Automated Pipeline for Robust Cat Activity Detection Based on Deep Learning and Wearable Sensor Data.

The health, safety, and well-being of household pets such as cats has become a challenging task in p...

Accuracy of deep learning-based attenuation correction in Tc-GSA SPECT/CT hepatic imaging.

INTRODUCTION: Attenuation correction (AC) is necessary for accurate assessment of radioactive distri...

A F-FDG PET/CT-based deep learning-radiomics-clinical model for prediction of cervical lymph node metastasis in esophageal squamous cell carcinoma.

BACKGROUND: To develop an artificial intelligence (AI)-based model using Radiomics, deep learning (D...

Brain imaging and machine learning reveal uncoupled functional network for contextual threat memory in long sepsis.

Positron emission tomography (PET) utilizes radiotracers like [F]fluorodeoxyglucose (FDG) to measure...

Investigation of scatter energy window width and count levels for deep learning-based attenuation map estimation in cardiac SPECT/CT imaging.

Deep learning (DL) is becoming increasingly important in generating attenuation maps for accurate at...

Edge Computing for AI-Based Brain MRI Applications: A Critical Evaluation of Real-Time Classification and Segmentation.

Medical imaging plays a pivotal role in diagnostic medicine with technologies like Magnetic Resonanc...

A novel meta learning based stacked approach for diagnosis of thyroid syndrome.

Thyroid syndrome, a complex endocrine disorder, involves the dysregulation of the thyroid gland, imp...

Using interpretable deep learning radiomics model to diagnose and predict progression of early AD disease spectrum: a preliminary [F]FDG PET study.

OBJECTIVES: In this study, we propose an interpretable deep learning radiomics (IDLR) model based on...

Tracer-Separator: A Deep Learning Model for Brain PET Dual-Tracer ( 18 F-FDG and Amyloid) Separation.

INTRODUCTION: Multiplexed PET imaging revolutionized clinical decision-making by simultaneously capt...

GeSeNet: A General Semantic-Guided Network With Couple Mask Ensemble for Medical Image Fusion.

At present, multimodal medical image fusion technology has become an essential means for researchers...

Clinical Pilot of a Deep Learning Elastic Registration Algorithm to Improve Misregistration Artifact and Image Quality on Routine Oncologic PET/CT.

RATIONALE AND OBJECTIVES: Misregistration artifacts between the PET and attenuation correction CT (C...

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