Radiology

Weakly semi-supervised cardiac MRI segmentation with frequency-domain pseudo label dynamic mixed supervision and partial-dice constraints.

Magnetic Resonance Imaging (MRI) of the heart provides precise visualization of cardiac anatomical structures, making accurate automatic segmentation highly valuable for assisting in the diagnosis of cardiovascular diseases. Numerous deep learning-based segmentation methods have been proposed to date. While these approaches have yielded promising results, most rely heavily on large-scale datasets ...

Comparing prostate diffusion weighted images reconstructed with a commercial deep-learning product to a deep learning phase corrected model at 1.5 T.

PURPOSE: To determine whether a new deep learning (DL) based phase corrected (DLPC) reconstruction model can enhance image quality of diffusion weighted images of the prostate acquired at 1.5 T compared to a commercially available DL based product. METHODS AND MATERIALS: A retrospective study of 30 consecutive patients undergoing conventional multiparametric MRI (mpMRI) of the prostate on a single...

Clinically oriented deep learning framework for automated vessel wall segmentation in black-blood MRI: a multi-center study.

OBJECTIVES: To develop and validate a clinically applicable deep learning framework for automated segmentation of intracranial and carotid vessel wall...

IDH Mutation Classification in Nonenhancing Gliomas: A Comparison of Habitat and Whole-Tumor Transfer Learning Strategies.

BACKGROUND: Isocitrate dehydrogenase (IDH) mutation status is an important biomarker for the diagnosis and management of nonenhancing gliomas, undersc...

Prognostic value of a combined model integrating clinical and PET radiomics parameters in metastatic melanoma: A dual-center retrospective study.

OBJECTIVES: To develop and evaluate the predictive efficacy of a combined model incorporating clinical parameters and PET-based radiomics signature (R...

Extreme cardiac MRI analysis under respiratory motion: Results of the CMRxMotion challenge.

Deep learning models have achieved state-of-the-art performance in automated Cardiac Magnetic Resonance (CMR) analysis. However, the efficacy of these...

Deep learning based CT grading system for sacroiliitis: a multi-center studydemonstrating superior accuracy and efficiency compared to human readers.

BACKGROUND: To develop and validate a deep convolutional neural network (DCNN) for automated sacroiliitis grading in axial spondyloarthritis (axSpA) u...

AI-aided diagnostic performance for prostate MRI: systematic review and meta-analysis.

BACKGROUND: AI is increasingly integrated within prostate cancer diagnosis pathway. PURPOSE: To provide estimates of diagnostic accuracy of AI assista...

Explainable machine learning algorithm for classifying resting-state functional MRI in amyotrophic lateral sclerosis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease that affects multiple brain systems. Altered brain function can b...

Machine learning pipeline for automated segmentation and classification of complicated cystic renal masses on MRI: comparison with radiologists' assessments.

PURPOSE: To develop and validate a machine learning (ML)-based pipeline for automated segmentation and classification of complicated cystic renal mass...

AI-supported opportunistic detection of vertebral fractures on routine CT scans: Diagnostic performance and clinical relevance.

BACKGROUND: Vertebral fractures (VFs) are among the most common osteoporotic fractures, yet they are frequently underdiagnosed and left untreated. The...

Deep Learning-Based Skin Lesion Classification: A CNN Approach on High-Frequency Ultrasound Imaging.

High-frequency ultrasound (HFUS) is valuable for assessing skin lesions, supporting diagnosis, treatment monitoring, and surgical planning. This study...

Deep Learning Reconstruction for 129Xe Diffusion-Weighted MRI Enables Use of Natural Abundant Xenon and Improved Image Acceleration.

PURPOSE: (i) To assess whether 129Xe apparent diffusion coefficient (ADC) and diffusive length scale (LmD) metrics are quantitatively preserved with d...

Low-count whole-body PET denoising with deep learning in a multicenter, multi-tracer and externally validated study.

BACKGROUND: Positron Emission Tomography (PET) is a powerful diagnostic tool, but its availability, high cost and radiation burden limit its accessibi...

Dynamic frame-by-frame motion correction for 18F-flurpiridaz PET-MPI using convolution neural network.

PURPOSE: Precise quantification of myocardial blood flow (MBF) and flow reserve (MFR) in 18F-flurpiridaz PET significantly relies on motion correction...

Choroidal volume decrease associated with stromal regression in adult myopia: A high-resolution optical coherence tomography angiography study.

PURPOSE: Observing choroidal volume changes in myopia with various degrees via spectral-domain optical coherence tomography (SD-OCT) images. METHODS: ...

Impact of Generative AI-Enhanced Low-Dose Cone-Beam Computed Tomography on Diagnosis and Treatment Planning for Impacted Mandibular Third Molars.

OBJECTIVES: To evaluate whether generative artificial intelligence (Gen-AI) could significantly enhance the visibility of the mandibular canal (MC) an...

Enhancing and accelerating brain MRI through deep learning reconstruction using prior subject-specific imaging.

Magnetic resonance imaging (MRI) is a crucial medical imaging modality. However, long acquisition times remain a significant challenge, leading to inc...

Integrating multiphase MRI surrogates to improve microvascular invasion detection and recurrence risk stratification in HCC.

BACKGROUND & AIMS: Microvascular invasion (MVI) is a key determinant of recurrence and poor outcomes in hepatocellular carcinoma (HCC), yet accurate p...

Learning curve for fenestrated-branched endovascular aortic repair using machine learning: A prospective national multicenter registry study.

OBJECTIVE: Fenestrated-branched endovascular aortic repair (F-BEVAR) is a complex procedure that requires significant experience and advanced technica...