Strokes

Depth-Sequence Transformer (DST) for Segment-Specific ICA Calcification Mapping on Non-Contrast CT

While total intracranial carotid artery calcification (ICAC) volume is an established stroke biomarker, growing evidence shows this aggregate metric ignores the critical influence of plaque location, since calcification in different segments carries distinct prognostic and procedural risks. However, a finer-grained, segment-specific quantification has remained technically infeasible. Conventiona...

Semi-supervised learning and integration of multi-sequence MR-images for carotid vessel wall and plaque segmentation

The analysis of carotid arteries, particularly plaques, in multi-sequence Magnetic Resonance Imaging (MRI) data is crucial for assessing the risk of atherosclerosis and ischemic stroke. In order to evaluate metrics and radiomic features, quantifying the state of atherosclerosis, accurate segmentation is important. However, the complex morphology of plaques and the scarcity of labeled data poses ...

Bleeding risk assessment tools in patients with atrial fibrillation taking anticoagulants: a comparative review and clinical implications.

INTRODUCTION: Bleeding risk assessment plays a critical role in the anticoagulation management for atrial fibrillation (AF), to balance stroke prevent...

ABCD: A Simulation Method for Accelerating Conversational Agents With Applications in Aphasia Therapy.

PURPOSE: Development of aphasia therapies is limited by clinician shortages, patient recruitment challenges, and funding constraints. To address these...

Prediction of tissue and clinical thrombectomy outcome in acute ischaemic stroke using deep learning.

The advent of endovascular thrombectomy has significantly improved outcomes for stroke patients with intracranial large vessel occlusion, yet individu...

An Advanced Deep Learning Framework for Ischemic and Hemorrhagic Brain Stroke Diagnosis Using Computed Tomography (CT) Images

Brain stroke is one of the leading causes of mortality and long-term disability worldwide, highlighting the need for precise and fast prediction tec...

Outcome prediction and individualized treatment effect estimation in patients with large vessel occlusion stroke

Mechanical thrombectomy has become the standard of care in patients with stroke due to large vessel occlusion (LVO). However, only 50% of successful...

Customizable ROI-Based Deep Image Compression

Region of Interest (ROI)-based image compression optimizes bit allocation by prioritizing ROI for higher-quality reconstruction. However, as the use...

Integrating AI/ML and multi-omics approaches to investigate the role of TNFRSF10A/TRAILR1 and its potential targets in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with a five-year survival of under 10 % despite current therapies...

Unravelling the brain resilience following stroke: From injury to rewiring of the brain through pathway activation, drug targets, and therapeutic interventions.

Synaptic plasticity is a neuron's intrinsic ability to make new connections throughout life. The morphology and function of synapses are highly suscep...

Impact of spectrum bias on deep learning-based stroke MRI analysis.

PURPOSE: To evaluate spectrum bias in stroke MRI analysis by excluding cases with uncertain acute ischemic lesions (AIL) and examining patient, imagin...

Prediction of post stroke depression with machine learning: A national multicenter cohort study.

OBJECTIVE: Post-stroke depression (PSD) is a common psychiatric complication following stroke, with low clinical detection rates and delayed diagnosis...

An informed machine learning based environmental risk score for hypertension in European adults.

BACKGROUND: The exposome framework seeks to unravel the cumulated effects of environmental exposures on health. However, existing methods struggle wit...

WordCon: Word-level Typography Control in Scene Text Rendering

Achieving precise word-level typography control within generated images remains a persistent challenge. To address it, we newly construct a word-lev...

Federated Learning for MRI-based BrainAGE: a multicenter study on post-stroke functional outcome prediction

$\textbf{Objective:}$ Brain-predicted age difference (BrainAGE) is a neuroimaging biomarker reflecting brain health. However, training robust BrainA...

Two-stage convolutional neural network for segmentation and detection of carotid web on CT angiography.

BACKGROUND: Carotid web (CaW) is a risk factor for ischemic stroke, mainly in young patients with stroke of undetermined etiology. Its detection is ch...

DWI-based deep learning radiomics nomogram for predicting the impaired quality of life in patients with unruptured intracranial aneurysm developing new iatrogenic cerebral infarcts following stent placement: a multicenter cohort study.

This study developed a DWI-based radiomics nomogram to predict impaired health-related quality of life (HRQOL) in patients with unruptured intracrania...

Stroke-based Cyclic Amplifier: Image Super-Resolution at Arbitrary Ultra-Large Scales

Prior Arbitrary-Scale Image Super-Resolution (ASISR) methods often experience a significant performance decline when the upsampling factor exceeds t...

Vectorized Region Based Brush Strokes for Artistic Rendering

Creating a stroke-by-stroke evolution process of a visual artwork tries to bridge the emotional and educational gap between the finished static artw...

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning

Reinforcement Learning with Verifiable Rewards (RLVR) has proven effective for training large language models (LLMs) on complex reasoning tasks, suc...