Radiology

Automated deep learning for real-time focal liver lesions detection in ultrasound videos a multicenter study.

Early detection of focal liver lesions (FLLs) is crucial for clinical practice, but ultrasound performance heavily depends on operator experience. We developed Auto-DFLLs, an automated deep learning model based on ResNet and FPN architectures to detect FLLs in ultrasound videos. It was trained and validated on 5258 prospectively collected videos from three hospitals. On internal validation, Auto-D...

A vision-language foundation model improves preoperative diagnosis of follicular thyroid neoplasms using ultrasound images.

Preoperative discrimination between follicular thyroid carcinoma (FTC) and follicular thyroid adenoma (FTA) remains challenging, as imaging and cytological approaches often show limited efficacy. Even fine-needle aspiration (FNA) biopsy and intraoperative frozen sections frequently fail to provide conclusive results. Thus, follicular thyroid neoplasms (FNs) typically necessitate complete surgical ...

LungNet: Leveraging state-space models with SE-enhanced skip connections for precise CT-based lung lesion segmentation.

Lung cancer, which accounted for 2.48 million new cases and 1.82 million deaths worldwide in 2022, continues to be the most lethal cancer across the g...

Region-guided decoupled fusion network for ultrasound-based classification of thyroid nodules with and without Hashimoto's thyroiditis.

RATIONALE AND OBJECTIVES: Differentiating benign from malignant thyroid nodules is particularly challenging in patients with Hashimoto's thyroiditis (...

A review of deep learning-based Unsupervised Anomaly Detection in brain MRI.

The manual assessment of brain Magnetic Resonance Imaging (MRI) scans can be labor-intensive and time-consuming for radiologists. Deep Learning method...

Towards interpretable AI in personalized medicine through a radiological-biological radiomics dictionary linking semantic Lung-RADS and imaging radiomics features.

BACKGROUND: Lung cancer remains the leading cause of cancer-related mortality worldwide, with survival largely dependent on early detection. Standard-...

MRI-driven multimodal deep learning approach for predicting pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer: A multicenter study.

OBJECTIVES: Achieving a pathological complete response (pCR) following neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal c...

Automated detection of superior mesenteric artery occlusion on post-contrast CT Using a 3D deep learning model.

PURPOSE: To develop and evaluate a 3D deep learning model for detecting superior mesenteric artery occlusion (SMAO) on post-contrast abdominal CT exam...

Enhancing biomedical optical volumetric imaging via self-supervised orthogonal learning.

Optical volumetric imaging grapples with inherent noise problems arising from photon budget constraints, light scattering, and space-bandwidth product...

Diagnostic performance of deep learning models on ultrasound images for distinguishing benign from malignant ovarian cysts.

BACKGROUND: Ovarian cysts are a common pelvic disorder in women, and accurate differentiation between benign and malignant types is essential for guid...

Magnetic resonance imaging-based radiomics of mesorectum for predicting extramural venous invasion in patients with rectal cancer: a bi-centric study.

OBJECTIVES: To develop and validate a magnetic resonance imaging (MRI)-based radiomics model of the mesorectum for predicting extramural venous invasi...

Cone-Beam Computed Tomography-Based Three-Dimensional Phenotypes of Skeletal Class II Malocclusion in Yemeni Adults: A Principal Component and Cluster Analysis.

INTRODUCTION AND AIMS: Skeletal Class II malocclusion is heterogeneous, and conventional two-dimensional cephalometry may not fully capture relevant t...

Decoupling Visual Parsing and Diagnostic Reasoning for Vision-Language Models (GPT-4o and GPT-5): Analysis Using Thoracic Imaging Quiz Cases.

BACKGROUND. Vision-language models (VLMs) have potential to identify findings on radiologic imaging (i.e., visual parsing) and translate findings into...

Integrating Machine Learning Tools in Protein Design: A Case of MHETase Engineering for PET Biodeconstruction.

The integration of machine learning tools into protein engineering offers substantial promise, yet linking computational predictions to experimental p...

MRI-Guided High-Intensity Focused Ultrasound in Movement Disorders: Targeting Pathologic Brain Circuits With Precision Imaging, From the AJR Special Series on Critical Anatomy.

MRI-guided high-intensity focused ultrasound (MRgHIFU) has emerged as an alternative to other neuromodulatory interventions for patients with medicall...

Commercial AI Model Diagnostic Accuracy for Intracranial Large- and Medium-Vessel Occlusion in Emergency CT Angiography.

The diagnostic accuracy of AIDOC-VO, the first commercial artificial intelligence tool for intracranial large-and medium-vessel occlusion (LVO/MeVO) d...

Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegeneration.

Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnetic resonance imaging (MRI). Brain aging involves m...

Application of artificial intelligence on magnetocardiology.

Early diagnosis and localization of the ischemic region are critical for effective treatment of ischemic heart disease (IHD), a condition which leads ...

Ethical and Legal Concerns of Deepfake Technology in Biomedical Imaging: A Comprehensive Survey.

Deepfakes have posed severe challenges to healthcare systems as fake medical images and videos can be utilized to disseminate fake information about a...

A Preliminary Study of a Machine Learning Prediction of Poorly Differentiated Hepatocellular Carcinoma Based on a Comprehensive Parameter Analysis Using Dual-Energy Computed Tomography.

OBJECTIVE: To develop and evaluate the performance of a predictive machine learning model for poorly differentiated hepatocellular carcinoma (p-HCC) u...