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Facial Botox Injection Point Detection Using YOLOv8 Enhanced with CBAM and BiFPN: A Multi-Perspective Deep Learning Approach
Facial Botox Injection Point Detection Using YOLOv8 Enhanced with CBAM and BiFPN: A Multi-Perspective Deep Learning Approach
Botox is one of the most frequently performed procedures in cosmetic dermatology, aimed at reducing wrinkles and enhancing...
Machine Learning for MRI Classification of Systemic Lupus Erythematous Patients with and without Neuropsychiatric Events
Machine Learning for MRI Classification of Systemic Lupus Erythematous Patients with and without Neuropsychiatric Events
To provide a useful and practical Machine Learning framework to facilitate the diagnosis of Neuropsychiatric Systemic Lupu...
Deep Learning-Based Multi-Stage System for Automated Tooth Detection and Segmentation in Orthodontic Photography
Deep Learning-Based Multi-Stage System for Automated Tooth Detection and Segmentation in Orthodontic Photography
This study aimed to develop and evaluate a fully automated, artificial intelligence–driven system for tooth detectio...
A Plugin-Based Architecture for Integrating AI Services in an Open-Source PACS
A Plugin-Based Architecture for Integrating AI Services in an Open-Source PACS
Automated image analysis, supported by powerful artificial intelligence algorithms, promises significant workflow advantag...
Artificial Intelligence Could Predict Chest Tube Drainage Necessity for Spontaneous Pneumothorax
Artificial Intelligence Could Predict Chest Tube Drainage Necessity for Spontaneous Pneumothorax
Artificial intelligence (AI) is increasingly utilized in the medical field, primarily for diagnostic purposes. Although AI...
BreasTransNeXt: An Enhanced Multi-Module Vision Transformer For Early Breast Cancer Diagnosis
BreasTransNeXt: An Enhanced Multi-Module Vision Transformer For Early Breast Cancer Diagnosis
Breast cancer (BC) represents the most common and one of the most lethal malignancies among women globally, ranking second...
Development of a 3D Convolutional Neural Network for the Triage of High-Priority Oral and Maxillofacial CBCT Scans
Development of a 3D Convolutional Neural Network for the Triage of High-Priority Oral and Maxillofacial CBCT Scans
This project aims to establish a triage system for oral and maxillofacial cone-beam computed tomography (CBCT) scans by de...
MTW-ICHNet: Multi-task Weakly Supervised Learning with Enhanced Feature Descriptor Learning for Intracranial Hemorrhage Diagnosis
MTW-ICHNet: Multi-task Weakly Supervised Learning with Enhanced Feature Descriptor Learning for Intracranial Hemorrhage Diagnosis
Current research on intracerebral hemorrhage (ICH) detection faces challenges regarding feature utilization efficiency and...
Artificial Intelligence and CT Neuroimaging in Dementia and Psychotic Disorders: A Viewpoint
Artificial Intelligence and CT Neuroimaging in Dementia and Psychotic Disorders: A Viewpoint
Psychotic disorders are marked by heterogeneity in symptoms and treatment response, yet efforts to develop clinically usef...
A Novel Hybrid Large Language Model Approach for Reporting Panoramic Radiographs and Performance Comparison with Current Large Language Models
A Novel Hybrid Large Language Model Approach for Reporting Panoramic Radiographs and Performance Comparison with Current Large Language Models
Large language models (LLMs) show potential in clinical reporting, yet current multimodal systems remain unreliable for in...
De-identification Strategy and Re-identification Risks for Facial Computed Tomography Images via Deep Learning
De-identification Strategy and Re-identification Risks for Facial Computed Tomography Images via Deep Learning
The aim is to develop and evaluate a deep learning–based selective de-identification method for head computed tomogr...
Deep Learning–Based Prediction of Visual Field Mean Deviation from Numeric OCT Data in Glaucoma
Deep Learning–Based Prediction of Visual Field Mean Deviation from Numeric OCT Data in Glaucoma
The purpose is to evaluate whether numeric optical coherence tomography (OCT) data can predict Humphrey Visual Field Analy...
Cervical Intraepithelial Neoplasia (CIN1-3) Disease Grading Using a Mixture of Experts Approach
Cervical Intraepithelial Neoplasia (CIN1-3) Disease Grading Using a Mixture of Experts Approach
Accurate grading of cervical intraepithelial neoplasia (CIN1–3) from colposcopic images is clinically critical yet c...
Open-Access Fully Automated Intravenous Contrast Detection and Body Part Classification for Computed Tomography Scans: The FALCON Model
Open-Access Fully Automated Intravenous Contrast Detection and Body Part Classification for Computed Tomography Scans: The FALCON Model
Presence of intravenous contrast on computed tomography (CT) scans is often unreliably documented, especially in large res...
An Effective Breast Cancer Classification System Using Multiple Feature Extraction Techniques with Multi-scale Attention-Based Feature Fusion Model
An Effective Breast Cancer Classification System Using Multiple Feature Extraction Techniques with Multi-scale Attention-Based Feature Fusion Model
Breast cancer ranks as the second leading cause of death in women. Early identification of breast cancer can significantly...
ITSRS: An Inverse Taylor Series Adaptive Loss Based on Synergized Regional-Structural Information for Medical Image Segmentation
ITSRS: An Inverse Taylor Series Adaptive Loss Based on Synergized Regional-Structural Information for Medical Image Segmentation
Medical image segmentation is fundamental for accurate diagnosis, treatment planning, and disease monitoring. The design o...
The Clinical Utility of Three-Dimensional Liver Modelling: A Multicenter Survey
The Clinical Utility of Three-Dimensional Liver Modelling: A Multicenter Survey
Pre-operative planning for complex liver surgery is constrained by 2D CT/MRI. Digital 3D liver models (3DL-RL) may improve...
Optimal Lossy Compression Scheme of 3D Volumetric Ultrasound Images For Remote Breast Cancer Screening
Optimal Lossy Compression Scheme of 3D Volumetric Ultrasound Images For Remote Breast Cancer Screening
While lossy compression is gaining acceptance in medical imaging research, its practical use remains limited due to the la...
BDU-Net: An Edge-Segmentation-Oriented U-Shaped Network for Pediatric Knee Joint Segmentation
BDU-Net: An Edge-Segmentation-Oriented U-Shaped Network for Pediatric Knee Joint Segmentation
The growth plate and articular cartilage are essential for children’s bone development. Precise segmentation of cart...
Vision Transformers-Based Deep Feature Generation Framework for Hydatid Cyst Classification in Computed Tomography Images
Vision Transformers-Based Deep Feature Generation Framework for Hydatid Cyst Classification in Computed Tomography Images
Hydatid cysts, caused by Echinococcus granulosus, form progressively enlarging fluid-filled cysts in organs like the liver...
Investigating the Potential of Generative AI Clinical Case-Based Simulations on Radiography Education: A Pilot Study
Investigating the Potential of Generative AI Clinical Case-Based Simulations on Radiography Education: A Pilot Study
Education for medical imaging technologists or radiographers in regional and rural areas often faces significant challenge...
Deep Learning Approach for Biomedical Image Classification
Deep Learning Approach for Biomedical Image Classification
Biomedical image classification is of paramount importance in enhancing diagnostic precision and improving patient outcome...
Leveraging Ensemble on Self-Supervised Techniques to Enhance Model Performance: A Regime Analysis
Leveraging Ensemble on Self-Supervised Techniques to Enhance Model Performance: A Regime Analysis
Dysphagia manifests a wide spectrum of effects on human health, ranging from mild symptoms like coughing to more severe is...
Inter-AI Agreement in Measuring Cine MRI-Derived Cardiac Function and Motion Patterns: A Pilot Study
Inter-AI Agreement in Measuring Cine MRI-Derived Cardiac Function and Motion Patterns: A Pilot Study
Manually analyzing a series of MRI images to obtain information about the heart’s motion is a time-consuming and lab...
Interpretable MRI Subregional Radiomics-Deep Learning Model for Preoperative Lymphovascular Invasion Prediction in Rectal Cancer: A Dual-Center Study
Interpretable MRI Subregional Radiomics-Deep Learning Model for Preoperative Lymphovascular Invasion Prediction in Rectal Cancer: A Dual-Center Study
Develop a fusion model based on explainable machine learning, combining multiparametric MRI subregional radiomics and deep...
ESE and Transfer Learning for Breast Tumor Classification
ESE and Transfer Learning for Breast Tumor Classification
In this study, we proposed a lightweight neural network architecture based on inverted residual network, efficient squeeze...
Classification of Renal Lesions by Leveraging Hybrid Features from CT Images Using Machine Learning Techniques
Classification of Renal Lesions by Leveraging Hybrid Features from CT Images Using Machine Learning Techniques
Renal cancer is amid the several reasons of increasing mortality rates globally, which can be reduced by early detection a...
An Adaptive Generative 3D VNet Model for Enhanced Monkeypox Lesion Classification Using Deep Learning and Augmented Image Fusion
An Adaptive Generative 3D VNet Model for Enhanced Monkeypox Lesion Classification Using Deep Learning and Augmented Image Fusion
As monkeypox is spreading rapidly, the incidence of monkeypox has been increasing in recent times. Therefore, it is very i...
Deep Learning for Osteoporosis Diagnosis Using Magnetic Resonance Images of Lumbar Vertebrae
Deep Learning for Osteoporosis Diagnosis Using Magnetic Resonance Images of Lumbar Vertebrae
This work uses T1, STIR, and T2 MRI sequences of the lumbar vertebrae and BMD measurements to identify osteoporosis using ...
Diagnostic Performance of Artificial Intelligence in Detecting and Distinguishing Pancreatic Ductal Adenocarcinoma via Computed Tomography: A Systematic Review and Meta-Analysis
Diagnostic Performance of Artificial Intelligence in Detecting and Distinguishing Pancreatic Ductal Adenocarcinoma via Computed Tomography: A Systematic Review and Meta-Analysis
We conducted a systematic review and meta-analysis in diagnostic performance of studies that tried to use artificial intel...
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