Radiology

Preoperative prediction of rectal Cancer staging combining MRI deep transfer learning, radiomics features, and clinical factors: accurate differentiation from stage T2 to T3.

BACKGROUND: This study evaluates the efficacy of integrating MRI deep transfer learning, radiomic si...

Enhancing the reliability of deep learning-based head and neck tumour segmentation using uncertainty estimation with multi-modal images.

Deep learning shows promise in autosegmentation of head and neck cancer (HNC) primary tumours (GTV-T...

Automatic pipeline for segmentation of LV myocardium on quantitative MR T1 maps using deep learning model and computation of radial T1 and ECV values.

Native T1 mapping is a non-invasive technique used for early detection of diffused myocardial abnorm...

Diagnostic performances of Claude 3 Opus and Claude 3.5 Sonnet from patient history and key images in Radiology's "Diagnosis Please" cases.

PURPOSE: The diagnostic performance of large language artificial intelligence (AI) models when utili...

Two-step optimization for accelerating deep image prior-based PET image reconstruction.

Deep learning, particularly convolutional neural networks (CNNs), has advanced positron emission tom...

Recent trends in AI applications for pelvic MRI: a comprehensive review.

Magnetic resonance imaging (MRI) is an essential tool for evaluating pelvic disorders affecting the ...

Gated SPECT-Derived Myocardial Strain Estimated From Deep-Learning Image Translation Validated From N-13 Ammonia PET.

RATIONALE AND OBJECTIVES: This study investigated the use of deep learning-generated virtual positro...

Automatic diagnosis for adenomyosis in ultrasound images by deep neural networks.

OBJECTIVE: To present a new noninvasive technique for automatic diagnosis of adenomyosis, using a no...

Transforming Health Care Landscapes: The Lever of Radiology Research and Innovation on Emerging Markets Poised for Aggressive Growth.

Advances in radiology are crucial not only to the future of the field but to medicine as a whole. He...

Intelligent skin-removal photoacoustic computed tomography for human based on deep learning.

Photoacoustic computed tomography (PACT) has centimeter-level imaging ability and can be used to det...

Aberrant migration features in primary skin fibroblasts of Huntington's disease patients hold potential for unraveling disease progression using an image based machine learning tool.

Huntington's disease (HD) is a complex neurodegenerative disorder with considerable heterogeneity in...

Soul: An OCTA dataset based on Human Machine Collaborative Annotation Framework.

Branch retinal vein occlusion (BRVO) is the most prevalent retinal vascular disease that constitutes...

The stroke outcome optimization project: Acute ischemic strokes from a comprehensive stroke center.

Stroke is a leading cause of disability, and Magnetic Resonance Imaging (MRI) is routinely acquired ...

Evaluation of multiple deep neural networks for detection of intracranial dural arteriovenous fistula on susceptibility weighted angiography imaging.

BACKGROUND: The natural history of intracranial dural arteriovenous fistula (DAVF) is variable and e...

Accelerating breast MRI acquisition with generative AI models.

OBJECTIVES: To investigate the use of the score-based diffusion model to accelerate breast MRI recon...

Development of machine learning models for fractional flow reserve prediction in angiographically intermediate coronary lesions.

BACKGROUND: Fractional flow reserve (FFR) represents the gold standard in guiding the decision to pr...

Cognitive vision: AI automation of the surgical eye in fluorescence angiography - correspondence.

Integrating MRI-based radiomics and clinicopathological features for preoperative prognostication of early-stage cervical adenocarcinoma patients: in comparison to deep learning approach.

OBJECTIVES: The roles of magnetic resonance imaging (MRI) -based radiomics approach and deep learnin...

Improved microvascular imaging with optical coherence tomography using 3D neural networks and a channel attention mechanism.

Skin microvasculature is vital for human cardiovascular health and thermoregulation, but its imaging...

Decoding pulsatile patterns of cerebrospinal fluid dynamics through enhancing interpretability in machine learning.

Analyses of complex behaviors of Cerebrospinal Fluid (CSF) have become increasingly important in dis...

MRI-based deep learning and radiomics for prediction of occult cervical lymph node metastasis and prognosis in early-stage oral and oropharyngeal squamous cell carcinoma: a diagnostic study.

INTRODUCTION: The incidence of occult cervical lymph node metastases (OCLNM) is reported to be 20-30...