Radiology

Development and Validation of a Biparametric MRI Deep Learning Radiomics Model with Clinical Characteristics for Predicting Perineural Invasion in Patients with Prostate Cancer.

RATIONALE AND OBJECTIVES: Perineural invasion (PNI) is an important prognostic biomarker for prostat...

Deep learning based detection and classification of fetal lip in ultrasound images.

OBJECTIVES: Fetal cleft lip is a common congenital defect. Considering the delicacy and difficulty o...

Artificial Intelligence in Pancreatic Image Analysis: A Review.

Pancreatic cancer is a highly lethal disease with a poor prognosis. Its early diagnosis and accurate...

Endobronchial Ultrasound-Based Support Vector Machine Model for Differentiating between Benign and Malignant Mediastinal and Hilar Lymph Nodes.

INTRODUCTION: The aim of the study was to establish an ultrasonographic radiomics machine learning m...

Application of a machine learning and optimization method to predict patellofemoral instability risk factors in children and adolescents.

PURPOSE: Conservative treatment remains the standard approach for first-time patellar dislocations. ...

A systematic review of deep learning-based spinal bone lesion detection in medical images.

Spinal bone lesions encompass a wide array of pathologies, spanning from benign abnormalities to agg...

DECNet: Dense embedding contrast for unsupervised semantic segmentation.

Unsupervised semantic segmentation is important for understanding that each pixel belongs to known c...

Robust visual question answering via polarity enhancement and contrast.

The Visual Question Answering (VQA) task is an important research direction in the field of artifici...

Comparative evaluation of image-based vs. text-based vs. multimodal AI approaches for automatic breast density assessment in mammograms.

BACKGROUND AND OBJECTIVES: In the last decade, there has been a growing interest in applying artific...

An XAI-enhanced efficientNetB0 framework for precision brain tumor detection in MRI imaging.

BACKGROUND: Accurately diagnosing brain tumors from MRI scans is crucial for effective treatment pla...

United States newspaper and online media coverage of artificial intelligence and radiology from 1998 to 2023.

OBJECTIVE: To evaluate the frequency and content of media coverage pertaining to artificial intellig...

The Potential and Pitfalls of GPT-4 in Radiologic Assessment.

The role of radiomics for predicting of lymph-vascular space invasion in cervical cancer patients based on artificial intelligence: a systematic review and meta-analysis.

The primary aim of this study was to conduct a methodical examination and assessment of the prognost...

Deep learning-assisted two-dimensional transperineal ultrasound for analyzing bladder neck motion in women with stress urinary incontinence.

BACKGROUND: No universally recognized transperineal ultrasound parameters are available for evaluati...

Deep coherence learning: An unsupervised deep beamformer for high quality single plane wave imaging in medical ultrasound.

Plane wave imaging (PWI) in medical ultrasound is becoming an important reconstruction method with h...

Decision-making processes in artificial intelligence applications in dentomaxillofacial radiology from the perspective of Wittgenstein.

Non-contrast CT radiomics-clinical machine learning model for futile recanalization after endovascular treatment in anterior circulation acute ischemic stroke.

OBJECTIVE: To establish a machine learning model based on radiomics and clinical features derived fr...

Exploring deep learning strategies for intervertebral disc herniation detection on veterinary MRI.

Intervertebral Disc Herniation (IVDH) is a common spinal disease in dogs, significantly impacting th...

Synthetic temporal bone CT generation from UTE-MRI using a cycleGAN-based deep learning model: advancing beyond CT-MR imaging fusion.

OBJECTIVES: The aim of this study is to develop a deep-learning model to create synthetic temporal b...

Deep learning reconstruction for coronary CT angiography in patients with origin anomaly, stent or bypass graft.

PURPOSE: To develop and validate a deep learning (DL)-model for automatic reconstruction for coronar...

The Application of Robotics in Cardiac Rehabilitation: A Systematic Review.

: Robotics is commonly used in the rehabilitation of neuro-musculoskeletal injuries and diseases. Wh...