Tag: Medical Imaging

A new resource-optimized neural architecture search framework automatically identifies a compact 3D U-Net model for prostate cancer segmentation from diffusion-weighted ...

A study in the International Journal of Legal Medicine evaluates deep learning models for estimating dental age and classifying legal ...

A prospective study in Cancer Imaging shows that super-resolution ultrasound improves the diagnostic accuracy of a modified CEUS LI-RADS framework ...

A new deep learning framework uses virtual imaging to improve the objective grading and prognostic stratification of lung adenocarcinoma from ...

A prospective study demonstrates that diffusion-weighted MRI can non-invasively assess inflammatory bowel disease activity by correlating ADC values with histopathological ...

General-purpose vision-language models converted CT scans into numerical features that predicted postoperative pathological AJCC stage groups in renal cell carcinoma ...

A systematic review of 14 studies finds that economic evaluations of AI in radiology are concentrated in high-income countries and ...

A predictive nomogram combining clinical parameters and computed tomography imaging features successfully differentiated benign from malignant solid pulmonary nodules measuring ...

A new lightweight AI framework integrates deep learning, ensemble methods, and semantic search to classify skin lesions with high accuracy ...

Researchers trained a deep neural network on clinical trial videos to predict colon capsule endoscopy positions across bowel segments over ...

Advanced CT scanning of Jeremy Bentham's preserved head reveals chronic toothache, severe jaw arthritis, and detailed preservation artifacts from his ...

A new AI algorithm called OSCAR has been validated to suggest optimal stent sizes for iliac artery interventions, demonstrating high ...

Researchers developed a hybrid machine learning pipeline using transfer-learned CT features to accurately predict postoperative pulmonary function without requiring baseline ...

Researchers have developed a diagnostic framework combining persistent homology and machine learning that detects COVID-19 in chest computed tomography scans ...

A systematic review of 28 studies reveals that radiomics models identify vulnerable carotid artery plaques more effectively than conventional stenosis ...

A new attention-based deep learning framework classifies Parkinson’s disease from resting-state EEG signals with high accuracy and provides interpretable sub-band ...

A retrospective study in Frontiers in Physiology found that integrating cardiometabolic data and MRI vascular features improved risk stratification for ...

A systematic review and meta-analysis reveals that artificial intelligence decision support significantly enhances fracture detection sensitivity for clinicians, delivering the ...

A Channel Dense Dense U-Generative Adversarial Network restored image quality and quantitative uptake accuracy in four-fold accelerated PSMA PET imaging ...

Researchers propose a reinforcement learning method that automatically selects which layers of a pretrained neural network to fine-tune for medical ...