Radiology

[A semi-supervised MRI image segmentation dual-network model for regions with ambiguous boundaries and heterogeneous regions].

OBJECTIVES: To construct a high-value region-guided dual-network semi-supervised segmentation method (HVASS) under extremely low labeling rates for addressing the challenges of heterogeneity and blurred boundaries in MRI tumor subregions and improving the accuracy and reliability of complex boundary segmentation for the heart and glioma. METHODS: HVASS employs a dual-network collaborative learning...

Updates on Imaging Modalities for the Diagnosis of Aortic Stenosis.

Aortic stenosis (AS) is the most common degenerative valvular disease in elderly patients and is linked to high morbidity and mortality. Accurate diagnosis and risk stratification are critical for effective management. Transthoracic echocardiography is the standard diagnostic tool, but its reliance on flow-dependent parameters can lead to inconsistent grading, especially in low-flow, low-gradient,...

Patient-safe radiological language: Reducing nocebo harm in orthopedic imaging reports.

As patients increasingly access radiology reports through electronic portals, imaging reports are no longer private technical communications between c...

Radiomics using generative adversarial network enhanced non-contrast computed tomography for gastric cancer diagnosis.

Objective.Non-contrast-enhanced computed tomography (NCCT) images have limited tissue resolution for gastric cancer diagnosis, while contrast-enhanced...

Deep learning-based PET/CT mixture-of-experts model for relapse risk stratification in relapsed/refractory classical hodgkin lymphoma: a multicenter study.

BACKGROUND: Relapsed/refractory classical Hodgkin lymphoma (R/R cHL) remains clinically challenging due to substantial heterogeneity in relapse risk. ...

Automated segmentation of postsurgical resection cavities on magnetic resonance imaging in focal epilepsy: A Multicentre Epilepsy Lesion Detection study.

OBJECTIVE: Quantitative assessment of extent of tissue resection following epilepsy surgery requires accurate delineation of the resection cavity on p...

3D Slicer-based preprocedural trajectory planning for transvenous mediastinal biopsy using automated segmentation: a technical note.

Histological diagnosis of mediastinal tumors can be challenging when safe puncture access is limited by adjacent airway and vascular structures. This ...

Reflectance Confocal Microscopy Versus Line-Field Confocal Optical Coherence Tomography in Facial and Scalp Lesions Suspicious for Basal Cell Carcinoma: A Histopathology-Referenced Multi-Reader Study.

BACKGROUND: Non-invasive imaging techniques can support assessment of lesions suspicious for basal cell carcinoma (BCC) when dermoscopy is inconclusiv...

Multicenter External Validation of an AI-Based Funduscopic Carotid Atherosclerosis Score and Assessment of Its Association With Coronary Artery Calcification: External Validation Study.

BACKGROUND: Screening for atherosclerosis is essential for early intervention, but conventional screening methods are often invasive and resource-inte...

Brain network biomarkers for diagnosis and clinical stratification in multiple sclerosis: a longitudinal study integrating individualised structural covariance MRI with high-density EEG.

BACKGROUND: Multiple sclerosis (MS) is increasingly recognised as a disorder of large-scale brain network reorganisation rather than a disease explain...

Influence of artificial intelligence on the performance of endosonographers in detection of solid pancreatic tumors: a tandem randomized video study.

BACKGROUND: This study aimed to evaluate the influence of a pre-commercial artificial intelligence (AI)-based software system on endosonographers' per...

Structural Connectivity Alterations Within Frontal Subregions in Parkinson's Disease: Implications for Motor Dysfunction.

RATIONALE AND OBJECTIVES: Parkinson's disease (PD) is characterized by disrupted basal ganglia-thalamo-cortical connectivity, yet how frontal network ...

A Governance Framework for Diagnostic Quality in Hospital-Radiology Joint Ventures.

RATIONALE AND OBJECTIVES: Hospital-radiology joint ventures (JVs) are forming at an accelerating pace as health systems seek to recapture outpatient i...

A Combined Clinical/MRI Deep Learning Model for Estimating Outcomes After Percutaneous Transforaminal Endoscopic Discectomy.

BACKGROUND: Percutaneous transforaminal endoscopic discectomy (PTED) is a common treatment for lumbar disc herniation (LDH), but postoperative recover...

Large-scale AI-guided liver malignancy diagnosis: multicenter study and a single-arm trial.

Liver malignancies are frequently evaluated on contrast-enhanced computed tomography (CE-CT), but missed or delayed diagnoses remain a clinically impo...

Automatic MRI-Based segmentation of ablation zones in spine and liver: A comparative study of network performance and influencing factors.

PURPOSE: Ablation therapies are a treatment option for cancer patients, particularly for conditions such as spinal metastases and liver tumors. Precis...

AI-assisted endoscopic detection of Helicobacter pylori infection in atrophic gastritis: a multicenter diagnostic study.

BACKGROUND: Convolutional neural network (CNN)-based artificial intelligence systems have demonstrated promise in detecting Helicobacter pylori (Hp) i...

CSF Cytokine Network Organization Predicts Progression Independent of Relapse and MRI Activity in Multiple Sclerosis.

OBJECTIVE: Progression independent of relapse activity is a major determinant of long-term disability in multiple sclerosis, but its immunopathologic ...

An segformer-mix vision transformer-based GIST segmentation in fused CT-PET images.

Accurate segmentation of gastrointestinal stromal tumour (GIST) is always challenging task due to tissues intestines may have similar intensity values...

Artificial Intelligence in Ultrasound Imaging: Opportunities for Improving Diagnostic Accuracy in Gulf Health Care.

Ultrasound imaging is widely used across cardiology, hepatology, obstetrics, breast and thyroid imaging, and emergency care because it is real-time, n...