Radiology

Real-time MRI-ultrasound image translation under limited paired data using a physically motivated conditional GAN.

Objective. Magnetic resonance imaging (MRI) and ultrasound (US) provide complementary anatomical and intraoperative information, yet their large appearance discrepancy makes cross-modality synthesis challenging. This study proposes a fast and physically consistent bidirectional MRI-US translation framework based on a conditional generative adversarial network (GAN).Approach. The generator adopts a...

Prediction of Ki-67 Status in Breast Cancer Using a Habitat-Guided 2.5D Multiparametric MRI Deep Learning Model.

OBJECTIVE: Intratumoral heterogeneity may limit the representativeness of biopsy-based Ki-67 assessment in breast cancer. We therefore developed and validated a habitat-guided 2.5D deep learning (DL) model based on multiparametric MRI for noninvasive preoperative prediction of high versus low Ki-67 expression. METHODS: This retrospective study enrolled 333 patients with invasive breast carcinoma f...

An AI-assisted Clinical Decision Support System for Green Classification of Cystocele on Dynamic Transperineal Ultrasound.

Green classification of cystocele on dynamic transperineal ultrasound (TPUS) remains operator-dependent because it requires manual frame selection and...

Annotation-efficient Semi-supervised and Active Learning for Breast Cancer Segmentation in DCE-MRI.

Accurate breast tumor segmentation in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is vital for diagnosis and treatment planning. De...

Energy-regularized self-supervised deep network for speckle noise reduction in optical coherence tomography.

Optical Coherence Tomography (OCT) speckle degrades the contrast and impairs automated analysis. Classical speckle suppression methods blur boundaries...

Deep learning predicts overall survival in high-grade meningioma using MRI and clinical data.

BACKGROUND: High-grademeningiomas (WHO II-III) recurfrequentlyand show wide variation in patient survival,yet clinicians still lack practical ways to ...

Cone Beam Computed Tomography-based Lung Function Imaging using Deep Learning for Functional Image-Guided Adaptative Radiation Therapy.

PURPOSE: Recent studies indicate that lung function can change significantly during radiation therapy (RT) course. However, additional function imagin...

Automated CEAP Classification of Venous Duplex Reports Using Multimodal Artificial Intelligence.

OBJECTIVE: To develop and internally validate a prototype multimodal artificial intelligence system for automated CEAP (Clinical, Etiological, Anatomi...

Lipoprotein(a) and the C-reactive protein-triglyceride-glucose index in relation to coronary lesion burden in patients with acute coronary syndrome.

BACKGROUND: Lipoprotein(a) [Lp(a)] reflects inherited atherothrombotic risk, whereas the C-reactive protein-triglyceride-glucose index (CTI) integrate...

Calibrating artificial intelligence against human expertise using femoral nerve segmentation on ultrasound: a consensus framework.

INTRODUCTION: Meaningful validation of artificial intelligence for medical image interpretation requires comparison against human expert performance, ...

Correcting Axial Length-Related Magnification Errors in Optical Coherence Tomography Angiography Improves Machine Learning Classification Performance in High Myopia.

BACKGROUND: To determine whether axial length-related magnification correction in optical coherence tomography angiography (OCTA) improves machine lea...

Multiparametric MRI-Based Ensemble Deep Learning for Preoperative Classification of Pituitary Neuroendocrine Tumor Subtypes.

RATIONALE AND OBJECTIVES: Pituitary neuroendocrine tumors (PitNETs) exhibit diverse biological behavior requiring accurate subtyping to guide treatmen...

A Review of the Use of Artificial Intelligence in Ophthalmology Imaging: Approximation to Ocular Histopathology.

Ophthalmic imaging has advanced to a level at which it can closely approximate key histopathological features of certain ocular tissues, changing the ...

Interleaved Imaging and Actuation for Real-Time MRI During Active Control of a Magnetically-Actuated Robotic Catheter.

OBJECTIVE: Magnetic Resonance Imaging (MRI)-guided robotic catheter interventions offer improved safety, visualization and control. Catheter actuation...

Leveraging Clinical Text and Class Conditioning for 3D Prostate MRI Generation.

OBJECTIVE: Latent diffusion models (LDM) could alleviate data scarcity challenges affecting machine learning development for medical imaging. However,...

VesMamba: Vessel Morphology-Enhanced State Space Model for Cerebrovascular Delineation.

Accurate delineation of cerebrovascular structures from Time-Of-Flight Magnetic Resonance Angiography (TOF-MRA) and Computed Tomography Angiography (C...

3D MR Fingerprinting for Quantitative Bladder Wall T1, T2, and M0 Mapping in Healthy Subjects at 1.5 T and 3 T.

Current diagnostic tests for lower urinary tract symptoms (LUTS) do not assess tissue-level alterations in the bladder wall. This study assesses the f...

CT-Guided Procedures: Tips and Tricks-A Practical Review for Contemporary Musculoskeletal Intervention.

Computed tomography (CT)-guided musculoskeletal interventions (MSK-CTg-IR) are integral to modern interventional radiology, offering precise anatomic ...

Dual-view scout scans with deep learning for ultra-low dose attenuation correction in PET.

BACKGROUND: Accurate attenuation correction (AC) is essential for quantitative positron emission tomography (PET). Conventional CT-based AC provides r...

Association Between Anterior Hippocampal Gyrification and Episodic Memory Performance in Neurotypical Young Adults.

The hippocampus is critical for episodic memory. The relationship between its structural variability and individual differences in episodic memory per...