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Teleradiology-Based Referrals for Patients with Gastroenterological Diseases Between Tertiary and Regional Hospitals: A Hospital-to-Hospital Approach
Teleradiology-Based Referrals for Patients with Gastroenterological Diseases Between Tertiary and Regional Hospitals: A Hospital-to-Hospital Approach
Teleradiology is recognized for fostering collaboration between regional and tertiary hospitals. However, its application ...
Out-of-Distribution Detection and Radiological Data Monitoring Using Statistical Process Control
Out-of-Distribution Detection and Radiological Data Monitoring Using Statistical Process Control
Machine learning (ML) models often fail with data that deviates from their training distribution. This is a significant co...
Investigation of ComBat Harmonization on Radiomic and Deep Features from Multi-Center Abdominal MRI Data
Investigation of ComBat Harmonization on Radiomic and Deep Features from Multi-Center Abdominal MRI Data
ComBat harmonization has been developed to remove non-biological variations for data in multi-center research applying art...
A Multi-step Integrative Workflow Implementation to Improve Documentation of Point of Care Ultrasound in Medical Intensive Care Unit
A Multi-step Integrative Workflow Implementation to Improve Documentation of Point of Care Ultrasound in Medical Intensive Care Unit
Point of care ultrasound (POCUS) provides quick bedside assessment for diagnosing and managing life-threatening conditions...
Automated ASPECTS Segmentation and Scoring Tool: a Method Tailored for a Colombian Telestroke Network
Automated ASPECTS Segmentation and Scoring Tool: a Method Tailored for a Colombian Telestroke Network
To evaluate our two non-machine learning (non-ML)-based algorithmic approaches for detecting early ischemic infarcts on br...
Septic Arthritis Modeling Using Sonographic Fusion with Attention and Selective Transformation: a Preliminary Study
Septic Arthritis Modeling Using Sonographic Fusion with Attention and Selective Transformation: a Preliminary Study
Conventionally diagnosing septic arthritis relies on detecting the causal pathogens in samples of synovial fluid, synovium...
Assessment of Age-Related Differences in Lower Leg Muscles Quality Using Radiomic Features of Magnetic Resonance Images
Assessment of Age-Related Differences in Lower Leg Muscles Quality Using Radiomic Features of Magnetic Resonance Images
Sarcopenia, characterised by a decline in muscle mass and strength, affects the health of the elderly, leading to increase...
Vital Characteristics Cellular Neural Network (VCeNN) for Melanoma Lesion Segmentation: A Biologically Inspired Deep Learning Approach
Vital Characteristics Cellular Neural Network (VCeNN) for Melanoma Lesion Segmentation: A Biologically Inspired Deep Learning Approach
Cutaneous melanoma is a highly lethal form of cancer. Developing a medical image segmentation model capable of accurately ...
Automated Three-Dimensional Imaging and Pfirrmann Classification of Intervertebral Disc Using a Graphical Neural Network in Sagittal Magnetic Resonance Imaging of the Lumbar Spine
Automated Three-Dimensional Imaging and Pfirrmann Classification of Intervertebral Disc Using a Graphical Neural Network in Sagittal Magnetic Resonance Imaging of the Lumbar Spine
This study aimed to develop a graph neural network (GNN) for automated three-dimensional (3D) magnetic resonance imaging (...
Convolutional Neural Networks for Segmentation of Pleural Mesothelioma: Analysis of Probability Map Thresholds (CALGB 30901, Alliance)
Convolutional Neural Networks for Segmentation of Pleural Mesothelioma: Analysis of Probability Map Thresholds (CALGB 30901, Alliance)
The purpose of this study was to evaluate the impact of probability map threshold on pleural mesothelioma (PM) tumor delin...
Deep Learning for Automated Classification of Hip Hardware on Radiographs
Deep Learning for Automated Classification of Hip Hardware on Radiographs
Purpose: To develop a deep learning model for automated classification of orthopedic hardware on pelvic and hip radiograph...
Sex-Specific Imaging Biomarkers for Parkinson’s Disease Diagnosis: A Machine Learning Analysis
Sex-Specific Imaging Biomarkers for Parkinson’s Disease Diagnosis: A Machine Learning Analysis
This study aimed to identify sex-specific imaging biomarkers for Parkinson’s disease (PD) based on multiple MRI morp...
A Novel Network for Low-Dose CT Denoising Based on Dual-Branch Structure and Multi-Scale Residual Attention
A Novel Network for Low-Dose CT Denoising Based on Dual-Branch Structure and Multi-Scale Residual Attention
Deep learning-based denoising of low-dose medical CT images has received great attention both from academic researchers an...
Screening Patient Misidentification Errors Using a Deep Learning Model of Chest Radiography: A Seven Reader Study
Screening Patient Misidentification Errors Using a Deep Learning Model of Chest Radiography: A Seven Reader Study
We aimed to evaluate the ability of deep learning (DL) models to identify patients from a paired chest radiograph (CXR) an...
Application of Wiener Filter Based on Improved BB Gradient Descent in Iris Image Restoration
Application of Wiener Filter Based on Improved BB Gradient Descent in Iris Image Restoration
Iris recognition, renowned for its exceptional precision, has been extensively utilized across diverse industries. However...
Unsupervised and Self-supervised Learning in Low-Dose Computed Tomography Denoising: Insights from Training Strategies
Unsupervised and Self-supervised Learning in Low-Dose Computed Tomography Denoising: Insights from Training Strategies
In recent years, X-ray low-dose computed tomography (LDCT) has garnered widespread attention due to its significant reduct...
Differences in Topography of Individual Amyloid Brain Networks by Amyloid PET Images in Healthy Control, Mild Cognitive Impairment, and Alzheimer’s Disease
Differences in Topography of Individual Amyloid Brain Networks by Amyloid PET Images in Healthy Control, Mild Cognitive Impairment, and Alzheimer’s Disease
Amyloid plaques, implicated in Alzheimer’s disease, exhibit a spatial propagation pattern through interconnected bra...
Detection of Diabetic Retinopathy Using Discrete Wavelet-Based Center-Symmetric Local Binary Pattern and Statistical Features
Detection of Diabetic Retinopathy Using Discrete Wavelet-Based Center-Symmetric Local Binary Pattern and Statistical Features
Computer-aided diagnosis (CAD) system assists ophthalmologists in early diabetic retinopathy (DR) detection by automating ...
Feasibility of Three-Dimension Chemical Exchange Saturation Transfer MRI for Predicting Tumor and Node Staging in Rectal Adenocarcinoma: An Exploration of Optimal ROI Measurement
Feasibility of Three-Dimension Chemical Exchange Saturation Transfer MRI for Predicting Tumor and Node Staging in Rectal Adenocarcinoma: An Exploration of Optimal ROI Measurement
To investigate the feasibility of predicting rectal adenocarcinoma (RA) tumor (T) and node (N) staging from an optimal ROI...
PelviNet: A Collaborative Multi-agent Convolutional Network for Enhanced Pelvic Image Registration
PelviNet: A Collaborative Multi-agent Convolutional Network for Enhanced Pelvic Image Registration
PelviNet introduces a groundbreaking multi-agent convolutional network architecture tailored for enhancing pelvic image re...
Dual-Tree Complex Wavelet Pooling and Attention-Based Modified U-Net Architecture for Automated Breast Thermogram Segmentation and Classification
Dual-Tree Complex Wavelet Pooling and Attention-Based Modified U-Net Architecture for Automated Breast Thermogram Segmentation and Classification
Thermography is a non-invasive and non-contact method for detecting cancer in its initial stages by examining the temperat...
Automatic Diagnosis of Hepatocellular Carcinoma and Metastases Based on Computed Tomography Images
Automatic Diagnosis of Hepatocellular Carcinoma and Metastases Based on Computed Tomography Images
Liver cancer, a leading cause of cancer mortality, is often diagnosed by analyzing the grayscale variations in liver tissu...
Correction: Certified Imaging Informatics Professionals (CIIP) Demonstrate Value to the Healthcare Industry and Focus on Quality Through the ABII 10-Year Requirements Practice Option
Correction: Certified Imaging Informatics Professionals (CIIP) Demonstrate Value to the Healthcare Industry and Focus on Quality Through the ABII 10-Year Requirements Practice Option
Cite this articleElahi, A., Fennell, N. & Watson, L. Correction: Certified Imaging Informatics Professionals (CIIP) De...
Improving the Annotation Process in Computational Pathology: A Pilot Study with Manual and Semi-automated Approaches on Consumer and Medical Grade Devices
Improving the Annotation Process in Computational Pathology: A Pilot Study with Manual and Semi-automated Approaches on Consumer and Medical Grade Devices
The development of reliable artificial intelligence (AI) algorithms in pathology often depends on ground truth provided by...
Feature-Based vs. Deep-Learning Fusion Methods for the In Vivo Detection of Radiation Dermatitis Using Optical Coherence Tomography, a Feasibility Study
Feature-Based vs. Deep-Learning Fusion Methods for the In Vivo Detection of Radiation Dermatitis Using Optical Coherence Tomography, a Feasibility Study
Acute radiation dermatitis (ARD) is a common and distressing issue for cancer patients undergoing radiation therapy, leadi...
Optimized Spatial Transformer for Segmenting Pancreas Abnormalities
Optimized Spatial Transformer for Segmenting Pancreas Abnormalities
The precise delineation of the pancreas from clinical images poses a substantial obstacle in the realm of medical image an...
The Fine-Tuned Large Language Model for Extracting the Progressive Bone Metastasis from Unstructured Radiology Reports
The Fine-Tuned Large Language Model for Extracting the Progressive Bone Metastasis from Unstructured Radiology Reports
Early detection of patients with impending bone metastasis is crucial for prognosis improvement. This study aimed to inves...
Predicting Pathological Characteristics of HER2-Positive Breast Cancer from Ultrasound Images: a Deep Ensemble Approach
Predicting Pathological Characteristics of HER2-Positive Breast Cancer from Ultrasound Images: a Deep Ensemble Approach
The objective is to evaluate the feasibility of utilizing ultrasound images in identifying critical prognostic biomarkers ...
Improved Automated Quality Control of Skeletal Wrist Radiographs Using Deep Multitask Learning
Improved Automated Quality Control of Skeletal Wrist Radiographs Using Deep Multitask Learning
Radiographic quality control is an integral component of the radiology workflow. In this study, we developed a convolution...
A 3D Convolutional Neural Network Based on Non-enhanced Brain CT to Identify Patients with Brain Metastases
A 3D Convolutional Neural Network Based on Non-enhanced Brain CT to Identify Patients with Brain Metastases
Dedicated brain imaging for cancer patients is seldom recommended in the absence of symptoms. There is increasing availabi...
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