Radiology

Integrating Artificial Intelligence into Prostate MR Imaging: Technical Foundations, Clinical Applications, and Workflow Implications.

Prostate MRI has become a cornerstone of contemporary prostate cancer diagnosis, enabling improved detection of clinically significant disease while reducing unnecessary biopsies and overtreatment. However, prostate MRI remains technically demanding, time-consuming, and subject to inter-reader variability, particularly as healthcare systems move toward abbreviated protocols such as non-contrast MR...

A convolutional neural network for fully automated total metabolic tumor volume delineation in patients with aggressive Non-Hodgkin lymphoma.

PURPOSE: The [18F]FDG-PET-derived total metabolic tumor volume (TMTV) has a high prognostic value in patients with Hodgkin and Non-Hodgkin lymphoma. However, in order to enable TMTV as a biomarker for clinical use, an accurate and fast method of tumor delineation in lymphoma patients is needed. Deep-learning-based methods have shown promising results in this field and offer distinct advantages ove...

A Parameter-free unsupervised framework for fMRI data analysis using batch learning growing neural gas and spatial-temporal false positive control.

BACKGROUND AND OBJECTIVE: Clustering methods are essential for analyzing functional magnetic resonance imaging (fMRI) time-series data to identify act...

The alteration of the brainstem functional connectivity in the first episode and drug-native generalized anxiety disorder and its transcriptional patterns.

BACKGROUND: Although the brainstem abnormality has been reported in anxiety disorders, there is a scarcity of research targeting the brainstem's funct...

Automated estimation of perivascular space and brain morphometry from deep learning-reconstructed three-dimensional T1-weighted MRI: comparison with the conventional technique.

PURPOSE: To evaluate the utility of deep learning-based reconstruction (DLR) three-dimensional T1-weighted imaging (T1-WI) in improving fine structura...

2D Multimodal Image Collection for Fluorescence Prediction from Transmitted Light Microscopy.

We present the Light My Cells Database, a large-scale open-access collection comprising 2,574 acquisition sets and 56,984 microscopy 2D images designe...

Adversarial AI reveals mechanisms and treatments for disorders of consciousness.

Understanding disorders of consciousness (DOC) remains one of the most challenging problems in neuroscience, hindered by the lack of experimental mode...

Machine learning vs. radiomics for discriminating atypical cartilaginous tumors from benign enchondromas on MRI.

BACKGROUND: Enchondromas (EC) present cartilaginous tumors that are difficult to differentiate from their intermediate counterpart, atypical cartilagi...

[Imaging modalities for corneal neovascularization].

Corneal neovascularization (CNV) is a frequent complication of many ocular surface diseases and represents a major threat to corneal transparency, vis...

Overall risk of cancer incidence attributable to adult body CT examinations: impact of a seven-year continuous quality improvement program.

OBJECTIVES: To estimate the impact of a continuous dose reduction and quality improvement program on radiation-induced cancer risk in adult computed t...

Artificial intelligence and radiomics in bladder cancer MRI: a scoping review of applications, performance, and barriers to clinical translation.

Artificial intelligence (AI) and radiomics show significant potential to augment bladder cancer (BC) MRI but face a critical translational gap. This s...

Deep learning reconstruction enables accelerated T2-weighted MRI for rectal cancer staging: a prospective study of diagnostic consistency across NEX value reduction.

OBJECTIVES: To evaluate the image quality, interpretation consistency, and scanning efficiency of deep learning-based reconstruction (DLR) algorithm (...

Best fast MRI protocols for the knee: advantages and limitations.

Knee MRI plays a central role in musculoskeletal diagnostics but has traditionally been associated with relatively long acquisition times. Recent tech...

PNET-PRISM: a multicenter-validated radiomics nomogram for noninvasive grading of pancreatic neuroendocrine tumors.

BACKGROUND: Accurate preoperative grading of pancreatic neuroendocrine tumors (PNETs) is essential for optimal treatment selection, yet endoscopic ult...

Integrated Implementation Strategies to Promote the Use of AI-Assisted Diagnostic Software for Lung Nodule Screening in China: Process Evaluation Based on the RE-AIM Framework.

BACKGROUND: While artificial intelligence (AI)-assisted diagnostic software holds promise for improving diagnostic efficiency and reducing disparities...

MRI-Based Synthetic CT Shows Promise as a Radiation-Free Alternative to Conventional CT in Orthopaedics.

➢ Computed tomography (CT) remains the gold standard for bone imaging, but radiation risks, especially in children, are driving interest in alternativ...

Radiology oral boards coach: A custom large language model prompt for structured oral board preparation in resident readouts.

With the reinstatement of the American Board of Radiology (ABR) oral board examination, optimal preparation strategies for the reinaugural classes rem...

HCLmNet: A unified hybrid continual learning strategy multimodal network for lung cancer survival prediction.

Lung cancer survival prediction remains one of the most challenging tasks in modern healthcare, as accurate and adaptive prediction models are essenti...

A pipeline for meso- and microplastic identification in aquatic systems using machine learning and hyperspectral imaging.

Microplastic pollution presents major environmental and health challenges, requiring accurate identification and quantification to assess its distribu...

Clinical priors-inspired privileged knowledge distillation for reliable pancreatic lesion classification.

Accurate classification of pancreatic lesions is critical for guiding treatment decisions, with computed tomography (CT) being the primary modality ow...