Radiology

SSAT-Swin: Deep Learning-Based Spinal Ultrasound Feature Segmentation for Scoliosis Using Self-Supervised Swin Transformer.

OBJECTIVE: Scoliosis, a 3-D spinal deformity, requires early detection and intervention. Ultrasound curve angle (UCA) measurement using ultrasound images has emerged as a promising diagnostic tool. However, calculating the UCA directly from ultrasound images remains challenging due to low contrast, high noise, and irregular target shapes. Accurate segmentation results are therefore crucial to enha...

Diagnostic Accuracy of a Deep Learning Algorithm for Detecting Unruptured Intracranial Aneurysms in Magnetic Resonance Angiography: A Multicenter Pivotal Trial.

BACKGROUND: Intracranial aneurysm rupture is associated with high mortality and disability rates. Early detection is crucial, but increasing diagnostic workloads place significant strain on radiologists. We evaluated the efficacy of a deep learning algorithm in detecting unruptured intracranial aneurysms (UIAs) using time-of-flight (TOF) magnetic resonance angiography (MRA).

Deep learning empowered gadolinium-free contrast-enhanced abbreviated MRI for diagnosing hepatocellular carcinoma.

BACKGROUND & AIMS: By reducing some magnetic resonance imaging (MRI) sequences, abbreviated MRI (aMRI) has shown extensive promise for detecting hepat...

Deep learning based automatic quantification of aortic valve calcification on contrast enhanced coronary CT angiography.

Quantifying aortic valve calcification is critical for assessing the severity of aortic stenosis, predicting cardiovascular risk, and guiding treatmen...

Deep learning radiomics for the prediction of epidermal growth factor receptor mutation status based on MRI in brain metastasis from lung adenocarcinoma patients.

BACKGROUND: Early and accurate identification of epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC) patient...

An interpretable machine learning model based on computed tomography radiomics for predicting programmed death ligand 1 expression status in gastric cancer.

BACKGROUND: Programmed death ligand 1 (PD-L1) expression status, closely related to immunotherapy outcomes, is a reliable biomarker for screening pati...

Metal Suppression Magnetic Resonance Imaging Techniques in Orthopaedic and Spine Surgery.

Implantation of metallic instrumentation is the mainstay of a variety of orthopaedic and spine surgeries. Postoperatively, imaging of the soft tissues...

The Role of AI in Lymphoma: An Update.

Malignant lymphomas encompass a range of malignancies with incidence rising globally, particularly with age. In younger populations, Hodgkin and Burki...

Using Machine Learning Models to Diagnose Chronic Rhinosinusitis: Analysis of Pre-Treatment Patient-Generated Health Data to Predict Cardinal Symptoms and Sinonasal Inflammation.

BackgroundThe diagnosis of chronic rhinosinusitis (CRS) relies upon patient-reported symptoms and objective nasal endoscopy and/or computed tomography...

Development of Artificial Intelligence-based Real-time Automatic Fusion of Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasonography of the Prostate.

OBJECTIVE: To report the development of artificial intelligence (AI)-based software to allow for the autonomous fusion of transrectal ultrasound and m...

Diagnostic performance of multimodal large language models in radiological quiz cases: the effects of prompt engineering and input conditions.

PURPOSE: This study aimed to evaluate the diagnostic accuracy of three multimodal large language models (LLMs) in radiological image interpretation an...

Applications of Artificial Intelligence in Constrictive Pericarditis: A Short Literature Review.

PURPOSE OF REVIEW: Constrictive pericarditis (CP) is a potentially curable condition characterized by the thickening, scarring, and calcification of t...

Enhancing cardiovascular risk prediction: the role of wall viscoelasticity in machine learning models.

This study aims to evaluate the significance of wall viscoelasticity in enhancing cardiovascular disease (CVD) risk prediction. We collected data on t...

Dual-Modality Virtual Biopsy System Integrating MRI and MG for Noninvasive Predicting HER2 Status in Breast Cancer.

RATIONALE AND OBJECTIVES: Accurate determination of human epidermal growth factor receptor 2 (HER2) expression is critical for guiding targeted therap...

Non-invasive derivation of instantaneous free-wave ratio from invasive coronary angiography using a new deep learning artificial intelligence model and comparison with human operators' performance.

Invasive coronary physiology is underused and carries risks/costs. Artificial Intelligence (AI) might enable non-invasive physiology from invasive cor...

Direct-to-Treatment Adaptive Radiation Therapy: Live Planning of Spine Metastases Using Novel Cone Beam Computed Tomography.

PURPOSE: Cone beam computed tomography (CBCT)-based online adaptive radiation therapy is carried out using a synthetic CT (sCT) created through deform...

Diagnostic value of deep learning of multimodal imaging of thyroid for TI-RADS category 3-5 classification.

BACKGROUND: Thyroid nodules classified within the Thyroid Imaging Reporting and Data Systems (TI-RADS) category 3-5 are typically regarded as having v...

DGEDDGAN: A dual-domain generator and edge-enhanced dual discriminator generative adversarial network for MRI reconstruction.

Magnetic resonance imaging (MRI) as a critical clinical tool in medical imaging, requires a long scan time for producing high-quality MRI images. To a...

The Road Map for ACR Practice Accreditation for Radiology Artificial Intelligence.

As the use of artificial intelligence (AI) continues to grow in radiology, it has become clear that its real-world performance often differs from that...

Extraction of pectin from watermelon rinds using sequential ultrasound-microwave technique: Optimization using RSM and ANN modeling and characterization.

This study aimed to optimize pectin extraction from watermelon (Citrullus lanatus) rind using sequential ultrasound-microwave assisted extraction (UMA...