AI Medical Compendium Journal:
Acta radiologica (Stockholm, Sweden : 1987)

Showing 31 to 40 of 45 articles

Application value of T2 fluid-attenuated inversion recovery sequence based on deep learning in static lacunar infarction.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Regular monitoring of static lacunar infarction (SLI) lesions plays an important role in preventing disease development and managing prognosis. Magnetic resonance imaging is one method used to monitor SLI lesions.

Integrating model explanations and hybrid priors into deep stacked networks for the "safe zone" prediction of acetabular cup.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Existing state-of-the-art "safe zone" prediction methods are statistics-based methods, image-matching techniques, and machine learning methods. Yet, those methods bring a tension between accuracy and interpretability.

Development of a deep learning-based auto-segmentation algorithm for hepatocellular carcinoma (HCC) and application to predict microvascular invasion of HCC using CT texture analysis: preliminary results.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Automatic segmentation has recently been developed to yield objective data. Prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC) using radiomics has been reported.

Automatic diagnosis and grading of patellofemoral osteoarthritis from the axial radiographic view: a deep learning-based approach.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Patellofemoral osteoarthritis (PFOA) has a high prevalence and is assessed on axial radiography of the patellofemoral joint (PFJ). A deep learning (DL)-based approach could help radiologists automatically diagnose and grade PFOA via inter...

Deep learning for automatic segmentation of paraspinal muscle on computed tomography.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Muscle quantification is an essential step in sarcopenia evaluation.

Comparison and verification of two deep learning models for the detection of chest CT rib fractures.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: A high false-positive rate remains a technical glitch hindering the broad spectrum of application of deep-learning-based diagnostic tools in routine radiological practice from assisting in diagnosing rib fractures.

Deep learning nomogram for predicting lymph node metastasis using computed tomography image in cervical cancer.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Deep learning (DL) has been used on medical images to grade, differentiate, and predict prognosis in many tumors.

Diagnostic performance and image quality of deep learning image reconstruction (DLIR) on unenhanced low-dose abdominal CT for urolithiasis.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Patients with urolithiasis undergo radiation overexposure from computed tomography (CT) scans. Improvement of image reconstruction is necessary for radiation dose reduction.