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Fibrous Tissue Semantic Segmentation in CT Images of Diffuse Interstitial Lung Disease
Fibrous Tissue Semantic Segmentation in CT Images of Diffuse Interstitial Lung Disease
Interstitial-lung-disease progression assessment and diagnosis via radiological findings on computed tomography images req...
Automatic Identification of Fetal Abdominal Planes from Ultrasound Images Based on Deep Learning
Automatic Identification of Fetal Abdominal Planes from Ultrasound Images Based on Deep Learning
Fetal biometric assessments through ultrasound diagnostics are integral in obstetrics and gynecology, requiring considerab...
Efficacy of Fine-Tuned Large Language Model in CT Protocol Assignment as Clinical Decision-Supporting System
Efficacy of Fine-Tuned Large Language Model in CT Protocol Assignment as Clinical Decision-Supporting System
Accurate CT protocol assignment is crucial for optimizing medical imaging procedures. The integration of large language mo...
The Effect of Ultrasound Image Pre-Processing on Radiomics Feature Quality: A Study on Shoulder Ultrasound
The Effect of Ultrasound Image Pre-Processing on Radiomics Feature Quality: A Study on Shoulder Ultrasound
Radiomics, the extraction of quantitative features from medical images, has shown great promise in enhancing diagnostic an...
Automating Prostate Cancer Grading: A Novel Deep Learning Framework for Automatic Prostate Cancer Grade Assessment using Classification and Segmentation
Automating Prostate Cancer Grading: A Novel Deep Learning Framework for Automatic Prostate Cancer Grade Assessment using Classification and Segmentation
Prostate Cancer (PCa) is the second most common cancer in men and affects more than a million people each year. Grading pr...
Impact of MRI Texture Analysis on Complication Rate in MRI-Guided Liver Biopsies
Impact of MRI Texture Analysis on Complication Rate in MRI-Guided Liver Biopsies
Magnetic resonance imaging (MRI)–derived texture features are quantitative imaging parameters that may have valuable...
A Deep-Learning Approach for Vocal Fold Pose Estimation in Videoendoscopy
A Deep-Learning Approach for Vocal Fold Pose Estimation in Videoendoscopy
Accurate vocal fold (VF) pose estimation is crucial for diagnosing larynx diseases that can eventually lead to VF paralysi...
3D Wasserstein Generative Adversarial Network with Dense U-Net-Based Discriminator for Preclinical fMRI Denoising
3D Wasserstein Generative Adversarial Network with Dense U-Net-Based Discriminator for Preclinical fMRI Denoising
Functional magnetic resonance imaging (fMRI) is extensively used in clinical and preclinical settings to study brain funct...
Application of a Commercial Artificial Intelligence Software in Unilateral Mammography: Simulating Total Mastectomy Scenarios
Application of a Commercial Artificial Intelligence Software in Unilateral Mammography: Simulating Total Mastectomy Scenarios
This study was to evaluate the performance of commercially available artificial intelligence (AI) software in unilateral m...
Hybrid Approach to Classifying Histological Subtypes of Non-small Cell Lung Cancer (NSCLC): Combining Radiomics and Deep Learning Features from CT Images
Hybrid Approach to Classifying Histological Subtypes of Non-small Cell Lung Cancer (NSCLC): Combining Radiomics and Deep Learning Features from CT Images
This study aimed to develop a hybrid model combining radiomics and deep learning features derived from computed tomography...
DECODE-3DViz: Efficient WebGL-Based High-Fidelity Visualization of Large-Scale Images using Level of Detail and Data Chunk Streaming
DECODE-3DViz: Efficient WebGL-Based High-Fidelity Visualization of Large-Scale Images using Level of Detail and Data Chunk Streaming
The DECODE-3DViz pipeline represents a major advancement in the web-based visualization of large-scale medical imaging dat...
Automated Grading of Vesicoureteral Reflux (VUR) Using a Dual-Stream CNN Model with Deep Supervision
Automated Grading of Vesicoureteral Reflux (VUR) Using a Dual-Stream CNN Model with Deep Supervision
Vesicoureteral reflux (VUR) is a urinary system disorder characterized by the abnormal flow of urine from the bladder back...
Impact of Combined Deep Learning Image Reconstruction and Metal Artifact Reduction Algorithm on CT Image Quality in Different Scanning Conditions for Maxillofacial Region with Metal Implants: A Phantom Study
Impact of Combined Deep Learning Image Reconstruction and Metal Artifact Reduction Algorithm on CT Image Quality in Different Scanning Conditions for Maxillofacial Region with Metal Implants: A Phantom Study
This study aims to investigate the impact of combining deep learning image reconstruction (DLIR) and metal artifacts reduc...
Estimating the Amount of Air Inside the Stomach for Detecting Cancers on Gastric Radiographs Using Artificial Intelligence: an Observational, Cross-sectional Study
Estimating the Amount of Air Inside the Stomach for Detecting Cancers on Gastric Radiographs Using Artificial Intelligence: an Observational, Cross-sectional Study
Gastric radiography is an important tool for early detection of cancer. During gastric radiography, the stomach is monitor...
Mainecoon: Implementing an Open-Source Web Viewer for DICOM Whole Slide Images with AI-Integrated PACS for Digital Pathology
Mainecoon: Implementing an Open-Source Web Viewer for DICOM Whole Slide Images with AI-Integrated PACS for Digital Pathology
The rapid advancement of digital pathology comes with significant challenges due to the diverse data formats from various ...
Dual-Domain Self-Supervised Deep Learning with Graph Convolution for Low-Dose Computed Tomography Reconstruction
Dual-Domain Self-Supervised Deep Learning with Graph Convolution for Low-Dose Computed Tomography Reconstruction
X-ray computed tomography (CT) is a commonly used imaging modality in clinical practice. Recent years have seen increasing...
Automated Neural Architecture Search for Cardiac Amyloidosis Classification from [18F]-Florbetaben PET Images
Automated Neural Architecture Search for Cardiac Amyloidosis Classification from [18F]-Florbetaben PET Images
Medical image classification using convolutional neural networks (CNNs) is promising but often requires extensive manual t...
Dual Energy CT for Deep Learning-Based Segmentation and Volumetric Estimation of Early Ischemic Infarcts
Dual Energy CT for Deep Learning-Based Segmentation and Volumetric Estimation of Early Ischemic Infarcts
Ischemic changes are not visible on non-contrast head CT until several hours after infarction, though deep convolutional n...
Empowering Women in Imaging Informatics: Confronting Imposter Syndrome, Addressing Microaggressions, and Striving for Work-Life Harmony
Empowering Women in Imaging Informatics: Confronting Imposter Syndrome, Addressing Microaggressions, and Striving for Work-Life Harmony
For the past 6 years, the Society for Imaging Informatics in Medicine (SIIM) annual meeting has provided a forum ...
Using Machine Learning on MRI Radiomics to Diagnose Parotid Tumours Before Comparing Performance with Radiologists: A Pilot Study
Using Machine Learning on MRI Radiomics to Diagnose Parotid Tumours Before Comparing Performance with Radiologists: A Pilot Study
The parotid glands are the largest of the major salivary glands. They can harbour both benign and malignant tumours. Preop...
Prediction of Malignancy and Pathological Types of Solid Lung Nodules on CT Scans Using a Volumetric SWIN Transformer
Prediction of Malignancy and Pathological Types of Solid Lung Nodules on CT Scans Using a Volumetric SWIN Transformer
Lung adenocarcinoma and squamous cell carcinoma are the two most common pathological lung cancer subtypes. Accurate diagno...
Deep Learning–Based Estimation of Radiographic Position to Automatically Set Up the X-Ray Prime Factors
Deep Learning–Based Estimation of Radiographic Position to Automatically Set Up the X-Ray Prime Factors
Radiation dose and image quality in radiology are influenced by the X-ray prime factors: KVp, mAs, and source-detector dis...
BCCHI-HCNN: Breast Cancer Classification from Histopathological Images Using Hybrid Deep CNN Models
BCCHI-HCNN: Breast Cancer Classification from Histopathological Images Using Hybrid Deep CNN Models
Breast cancer is the most common cancer in women globally, imposing a significant burden on global public health due to hi...
A Machine Learning Model Based on Global Mammographic Radiomic Features Can Predict Which Normal Mammographic Cases Radiology Trainees Find Most Difficult
A Machine Learning Model Based on Global Mammographic Radiomic Features Can Predict Which Normal Mammographic Cases Radiology Trainees Find Most Difficult
This study aims to investigate whether global mammographic radiomic features (GMRFs) can distinguish hardest- from easiest...
An Adaptive SCG-ECG Multimodal Gating Framework for Cardiac CTA
An Adaptive SCG-ECG Multimodal Gating Framework for Cardiac CTA
Cardiovascular disease (CVD) is the leading cause of death worldwide. Coronary artery disease (CAD), a prevalent form of C...
Transformer-Integrated Hybrid Convolutional Neural Network for Dose Prediction in Nasopharyngeal Carcinoma Radiotherapy
Transformer-Integrated Hybrid Convolutional Neural Network for Dose Prediction in Nasopharyngeal Carcinoma Radiotherapy
Radiotherapy is recognized as the major treatment of nasopharyngeal carcinoma. Rapid and accurate dose prediction can impr...
Foundational Segmentation Models and Clinical Data Mining Enable Accurate Computer Vision for Lung Cancer
Foundational Segmentation Models and Clinical Data Mining Enable Accurate Computer Vision for Lung Cancer
This study aims to assess the effectiveness of integrating Segment Anything Model (SAM) and its variant MedSAM into the au...
Myocardial Transit Time Mapping by CMR: A Novel Indicator of Microcirculatory Dysfunction in Cardiac Amyloidosis
Myocardial Transit Time Mapping by CMR: A Novel Indicator of Microcirculatory Dysfunction in Cardiac Amyloidosis
Cardiac amyloidosis (CA) is characterized by the deposition of amyloid fibrils within the myocardium, resulting in a restr...
Artificial Intelligence Application in Skull Bone Fracture with Segmentation Approach
Artificial Intelligence Application in Skull Bone Fracture with Segmentation Approach
This study aims to evaluate an AI model designed to automatically classify skull fractures and visualize segmentation on e...
A Novel Radiology Communication Tool to Reduce Workflow Interruptions: Clinical Evaluation of RadConnect
A Novel Radiology Communication Tool to Reduce Workflow Interruptions: Clinical Evaluation of RadConnect
Despite the importance of communication, radiology departments often depend on communication tools that were not created f...
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