Radiology

Imaging for Scapholunate Ligament Injuries: Techniques, Challenges, and Innovations.

Scapholunate (SL) ligament injuries are a common cause of wrist pain and instability but can be diagnostically challenging. Standard radiographs, ultrasound, computed tomography, and magnetic resonance imaging have been used for many years to assist in the diagnosis of these injuries, and all of them have benefits and limitations. Advanced dynamic modalities, such as real-time magnetic resonance i...

3D-QALAS synthetic MRI with Zero-DeepSub in children: initial experience including post-contrast imaging feasibility.

BACKGROUND: Magnetic resonance imaging (MRI) in children requires multiple sequences, leading to lengthy exams and motion-related challenges. Synthetic MRI generates multiple contrasts from a single acquisition, and integration of 3D-quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS) sequence with scan-specific deep-learning-based subspace r...

Prediction of Fontan failure and correlates of Fontan-associated liver disease severity using machine learning and radiomic features from multi-parametric abdominal MRI.

BACKGROUND: Fontan-associated liver disease (FALD) is associated with morbidity and mortality in patients with palliated single ventricle congenital h...

Applications of the Non-invasive Skin Imaging Techniques and Image-based Artificial Intelligence in Rosacea: A Narrative Review.

BACKGROUND: Rosacea is a common chronic inflammatory dermatosis with complex pathophysiology and heterogeneous clinical manifestations. Despite its pr...

CCE-Net: A Lightweight Context Contrast Enhancement Network and Its Application in Medical Image Segmentation.

Efficient and accurate image segmentation models play a vital role in medical image segmentation, however, high computational cost of traditional mode...

DBFANet: a dual-branch feature alignment network for automated detection of breast cancer bone metastasis.

Bone scan imaging for the detection of bone metastasis of breast cancer has been widely adopted; however, noise, anatomy superimposition, and small si...

A rapid and accurate guanidine CEST imaging in ischemic stroke using a machine learning approach.

OBJECTIVE: Rapid and accurate mapping of brain tissue pH is crucial for early diagnosis and management of ischemic stroke. Amide proton transfer (APT)...

Development and validation of an artificial intelligence-based model for diagnosing benign, borderline, and malignant adnexal masses.

Classification of benign, borderline, and malignant adnexal masses is critical to effective clinical management, but remains a challenge. We developed...

Detection of Swallowing Abnormalities in Pediatric FEES Recordings Using Rule-Based and Model-Based Methods.

Pediatric swallowing dysfunction (SwD) poses serious health risks, including aspiration, malnutrition, and recurrent respiratory infections, making ea...

Advances in cartilage imaging techniques.

Articular cartilage is crucial for joint function; however, it has limited regenerative capacity when damaged, a hallmark of many rheumatic diseases. ...

Integrating deep learning and radiomics for precise identification of luminal A/B breast cancer subtypes on dynamic contrast-enhanced MRI.

BACKGROUND: Accurate differentiation between luminal A and B subtypes of breast cancer is critical for selecting therapeutic strategies. However, curr...

Pediatric coronary MR angiography with a two-minute scan using de-aliasing regularization based compressed sensing.

BACKGROUND: Long acquisition time limits the clinical utility of coronary magnetic resonance angiography (CMRA) in pediatric populations. While deep l...

DeepVBM: A fully automatic and efficient voxel-based morphometry via deep learning-based segmentation and registration methods.

Voxel-based morphometry (VBM) using T1-weighted magnetic resonance imaging is a pivotal tool for assessing brain structure and identifying subtle morp...

Reablation of atrial fibrillation targeting electrogram dispersion in patients with isolated veins: The RESTART trial.

BACKGROUND: Pulmonary vein (PV) isolation is a well-established treatment for atrial fibrillation (AF), however, strategies for patients with recurren...

Micro-/nanorobots in nanomedicine - Guidance, imaging and the integration of AI and robotics.

The integration of robotics and artificial intelligence (AI) into nanomedicine represents a significant advancement in developing targeted therapeutic...

Machine Learning-based Radiomic Model for Early Diagnosis of Male Urethral Injury in Pelvic Fracture Patients.

BACKGROUND AND OBJECTIVE: Pelvic fracture urethral injury (PFUI) is serious and requires prompt diagnosis. Traditional diagnostic methods, which rely ...

Noninvasive skin imaging of melanocytic and nonmelanocytic tumours: recent findings.

PURPOSE OF REVIEW: Early diagnosis of skin cancer is essential for patient care. Noninvasive skin imaging devices have become increasingly used for th...

Artificial Intelligence-based detection of neuropsychiatric lupus: an exploratory meta-analysis of neuroimaging and multimodal biomarker models.

Neuropsychiatric systemic lupus erythematosus (NPSLE) remains challenging to diagnose because of heterogeneous clinical presentations, nonspecific fin...

An integrative deep learning model based on dual-mode ultrasound for diagnosing gallbladder polyps.

OBJECTIVES: The aim of this study was to develop an artificial intelligence model to automatically differentiate between non-neoplastic and neoplastic...

Interpretable MRI-Based Machine Learning Model for Noninvasive Prediction of Axillary Lymph Node Metastasis After Neoadjuvant Chemotherapy in Breast Cancer.

RATIONALE AND OBJECTIVES: Accurate prediction of axillary lymph node metastasis (ALNM) after neoadjuvant chemotherapy (NAC) remains challenging in bre...