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Deep Learning Approaches for Brain Tumor Detection and Classification Using MRI Images (2020 to 2024): A Systematic Review
Deep Learning Approaches for Brain Tumor Detection and Classification Using MRI Images (2020 to 2024): A Systematic Review
Brain tumor is a type of disease caused by uncontrolled cell proliferation in the brain leading to serious health issues s...
A Robust [18F]-PSMA-1007 Radiomics Ensemble Model for Prostate Cancer Risk Stratification
A Robust [18F]-PSMA-1007 Radiomics Ensemble Model for Prostate Cancer Risk Stratification
The aim of this study is to investigate the role of [18F]-PSMA-1007 PET in differentiating high- and low-risk prostate can...
MobileNet-V2: An Enhanced Skin Disease Classification by Attention and Multi-Scale Features
MobileNet-V2: An Enhanced Skin Disease Classification by Attention and Multi-Scale Features
The increasing prevalence of skin diseases necessitates accurate and efficient diagnostic tools. This research introduces ...
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...
A Lightweight Method for Breast Cancer Detection Using Thermography Images with Optimized CNN Feature and Efficient Classification
A Lightweight Method for Breast Cancer Detection Using Thermography Images with Optimized CNN Feature and Efficient Classification
Breast cancer is a prominent cause of death among women worldwide. Infrared thermography, due to its cost-effectiveness an...
Leveraging Ensemble Models and Follow-up Data for Accurate Prediction of mRS Scores from Radiomic Features of DSC-PWI Images
Leveraging Ensemble Models and Follow-up Data for Accurate Prediction of mRS Scores from Radiomic Features of DSC-PWI Images
Predicting long-term clinical outcomes based on the early DSC PWI MRI scan is valuable for prognostication, resource manag...
Deep Conformal Supervision: Leveraging Intermediate Features for Robust Uncertainty Quantification
Deep Conformal Supervision: Leveraging Intermediate Features for Robust Uncertainty Quantification
Trustworthiness is crucial for artificial intelligence (AI) models in clinical settings, and a fundamental aspect of trust...
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...
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...
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...
Discrimination of Left Atrial Strain Patterns in Hypertensive Heart Disease and Hypertrophic Cardiomyopathy: a Cardiac Magnetic Resonance Feature
Discrimination of Left Atrial Strain Patterns in Hypertensive Heart Disease and Hypertrophic Cardiomyopathy: a Cardiac Magnetic Resonance Feature
To assess left atrial (LA) strain parameters using cardiovascular magnetic resonance imaging feature tracking (cardiac MRI...
The Application of ImageJ Software for Roughness Analysis of Dental Implants
The Application of ImageJ Software for Roughness Analysis of Dental Implants
ImageJ software is a versatile, open-source software for visualizing, processing, and analyzing images, which has contribu...
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...
RDLR: A Robust Deep Learning-Based Image Registration Method for Pediatric Retinal Images
RDLR: A Robust Deep Learning-Based Image Registration Method for Pediatric Retinal Images
Retinal diseases stand as a primary cause of childhood blindness. Analyzing the progression of these diseases requires clo...
Image Analysis Using the Fluorescence Imaging of Nuclear Staining (FINS) Algorithm
Image Analysis Using the Fluorescence Imaging of Nuclear Staining (FINS) Algorithm
Finding appropriate image analysis techniques for a particular purpose can be difficult. In the context of the analysis of...
Prediction of Tumor-Associated Macrophages and Immunotherapy Benefits Using Weakly Supervised Contrastive Learning in Breast Cancer Pathology Images
Prediction of Tumor-Associated Macrophages and Immunotherapy Benefits Using Weakly Supervised Contrastive Learning in Breast Cancer Pathology Images
The efficacy of immune checkpoint inhibitors is significantly influenced by the tumor immune microenvironment (TIME). RNA ...
Advanced Gastric Cancer: CT Radiomics Prediction of Lymph Modes Metastasis After Neoadjuvant Chemotherapy
Advanced Gastric Cancer: CT Radiomics Prediction of Lymph Modes Metastasis After Neoadjuvant Chemotherapy
This study aims to create and assess machine learning models for predicting lymph node metastases following neoadjuvant tr...
Removing Adversarial Noise in X-ray Images via Total Variation Minimization and Patch-Based Regularization for Robust Deep Learning-based Diagnosis
Removing Adversarial Noise in X-ray Images via Total Variation Minimization and Patch-Based Regularization for Robust Deep Learning-based Diagnosis
Deep learning has significantly advanced the field of radiology-based disease diagnosis, offering enhanced accuracy and ef...
Evolutionary Strategies AI Addresses Multiple Technical Challenges in Deep Learning Deployment: Proof-of-Principle Demonstration for Neuroblastoma Brain Metastasis Detection
Evolutionary Strategies AI Addresses Multiple Technical Challenges in Deep Learning Deployment: Proof-of-Principle Demonstration for Neuroblastoma Brain Metastasis Detection
Two significant obstacles hinder the advancement of Radiology AI. The first is the challenge of overfitting, where small t...
Artificial Intelligence for Otosclerosis Detection: A Pilot Study
Artificial Intelligence for Otosclerosis Detection: A Pilot Study
The gold standard for otosclerosis diagnosis, aside from surgery, is high-resolution temporal bone computed tomography (TB...
Deep Learning for Describing Breast Ultrasound Images with BI-RADS Terms
Deep Learning for Describing Breast Ultrasound Images with BI-RADS Terms
Breast cancer is the most common cancer in women. Ultrasound is one of the most used techniques for diagnosis, but an expe...
Value of MRI - T2 Mapping to Differentiate Clinically Significant Prostate Cancer
Value of MRI - T2 Mapping to Differentiate Clinically Significant Prostate Cancer
Standardized reporting of multiparametric prostate MRI (mpMRI) is widespread and follows international standards (Pi-RADS)...
ISLE: An Intelligent Streaming Framework for High-Throughput AI Inference in Medical Imaging
ISLE: An Intelligent Streaming Framework for High-Throughput AI Inference in Medical Imaging
As the adoption of artificial intelligence (AI) systems in radiology grows, the increase in demand for greater bandwidth a...
Detection and Localization of Spine Disorders from Plain Radiography
Detection and Localization of Spine Disorders from Plain Radiography
Spine disorders can cause severe functional limitations, including back pain, decreased pulmonary function, and increased ...
Automated Segmentation of Lymph Nodes on Neck CT Scans Using Deep Learning
Automated Segmentation of Lymph Nodes on Neck CT Scans Using Deep Learning
Early and accurate detection of cervical lymph nodes is essential for the optimal management and staging of patients with ...
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