Radiology

A non-invasive diagnostic approach for neuroblastoma utilizing preoperative enhanced computed tomography and deep learning techniques.

Neuroblastoma presents a wide variety of clinical phenotypes, demonstrating different levels of benignity and malignancy among its subtypes. Early diagnosis is essential for effective patient management. Computed tomography (CT) serves as a significant diagnostic tool for neuroblastoma, utilizing machine vision imaging, which offers advantages over traditional X-ray and ultrasound imaging modaliti...

A deep learning-based multimodal medical imaging model for breast cancer screening.

In existing breast cancer prediction research, most models rely solely on a single type of imaging data, which limits their performance. To overcome this limitation, the present study explores breast cancer prediction models based on multimodal medical images (mammography and ultrasound images) and compares them with single-modal models. We collected medical imaging data from 790 patients, includi...

Performance of ChatGPT and Microsoft Copilot in Bing in answering obstetric ultrasound questions and analyzing obstetric ultrasound reports.

To evaluate and compare the performance of publicly available ChatGPT-3.5, ChatGPT-4.0 and Microsoft Copilot in Bing (Copilot) in answering obstetric ...

A multi-task neural network for full waveform ultrasonic bone imaging.

BACKGROUND AND OBJECTIVE: It is a challenging task to use ultrasound for bone imaging, as the bone tissue has a complex structure with high acoustic i...

Enhancing Patient Acceptance of Robotic Ultrasound through Conversational Virtual Agent and Immersive Visualizations.

Robotic ultrasound systems have the potential to improve medical diagnostics, but patient acceptance remains a key challenge. To address this, we prop...

SensARy Substitution: Augmented Reality Techniques to Enhance Force Perception in Touchless Robot Control.

The lack of haptic feedback in touchless human-robot interaction is critical in applications such as robotic ultrasound, where force perception is cru...

Breast tumour classification in DCE-MRI via cross-attention and discriminant correlation analysis enhanced feature fusion.

AIM: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has proven to be highly sensitive in diagnosing breast tumours, due to the kinetic...

A review of multimodal fusion-based deep learning for Alzheimer's disease.

Alzheimer's Disease (AD) as one of the most prevalent neurodegenerative disorders worldwide, characterized by significant memory and cognitive decline...

perfDSA: Automatic Perfusion Imaging in Cerebral Digital Subtraction Angiography.

PURPOSE: Cerebral digital subtraction angiography (DSA) is a standard imaging technique in image-guided interventions for visualizing cerebral blood f...

Variational mode directed deep learning framework for breast lesion classification using ultrasound imaging.

Breast cancer is the most prevalent cancer and the second cause of cancer related death among women in the United States. Accurate and early detection...

Pruning Sparse Tensor Neural Networks Enables Deep Learning for 3D Ultrasound Localization Microscopy.

Ultrasound Localization Microscopy (ULM) is a non-invasive technique that allows for the imaging of micro-vessels in vivo, at depth and with a resolut...

Artificial intelligence for children with attention deficit/hyperactivity disorder: a scoping review.

Attention deficit/hyperactivity disorder is a common neuropsychiatric disorder that affects around 5%-7% of children worldwide. Artificial intelligenc...

Dynamic simulation of knee joint mechanics: individualized multi-moment finite element modelling of patellar tendon stress during landing.

Patellar tendinopathy is prevalent in sports requiring high jumping demands, and understanding the in vivo biomechanical behavior of the patellar tend...

Challenges and Opportunities: Nanomaterials in Epilepsy Diagnosis.

Epilepsy is a common neurological disorder characterized by a significant rate of disability. Accurate early diagnosis and precise localization of the...

EfficientNet-Based Attention Residual U-Net With Guided Loss for Breast Tumor Segmentation in Ultrasound Images.

OBJECTIVE: Breast cancer poses a major health concern for women globally. Effective segmentation of breast tumors for ultrasound images is crucial for...

Plaque burden improves the detection of ischemic CAD over stenosis from coronary computed tomography angiography.

In symptomatic patients undergoing coronary CTA for suspected coronary artery disease (CAD), we assessed if quantification of plaque burden, in additi...

A semi-supervised prototypical network for prostate lesion segmentation from multimodality MRI.

Prostate lesion segmentation from multiparametric magnetic resonance images is particularly challenging due to the limited availability of labeled dat...

Artificial intelligence real-time automated recognition of the gastric antrum cross-sectional area and motility rhythm via bedside ultrasound: a pilot study.

The cross-sectional area (CSA) of the gastric antrum and its motility rhythm reflects the gastrointestinal function of critically ill patients. Monito...

Waveform-Specific Performance of Deep Learning-Based Super-Resolution for Ultrasound Contrast Imaging.

Resolving arterial flows is essential for understanding cardiovascular pathologies, improving diagnosis, and monitoring patient condition. Ultrasound ...

MM-UKAN++: A Novel Kolmogorov-Arnold Network-Based U-Shaped Network for Ultrasound Image Segmentation.

Ultrasound (US) imaging is an important and commonly used medical imaging modality. Accurate and fast automatic segmentation of regions of interest (R...