Radiology

Latest AI and machine learning research in radiology for healthcare professionals.

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A Hybrid Model of Feature Extraction and Dimensionality Reduction Using ViT, PCA, and Random Forest for Multi-Classification of Brain Cancer.

The brain serves as the central command center for the nervous system in the human body and is made...

An Information-Extreme Algorithm for Universal Nuclear Feature-Driven Automated Classification of Breast Cancer Cells.

Breast cancer diagnosis heavily relies on histopathological assessment, which is prone to subjectiv...

Multi-center evaluation of radiomics and deep learning to stratify malignancy risk of IPMNs.

Distinguishing high-risk intraductal papillary mucinous neoplasms (IPMNs), pancreatic cysts requirin...

Developing an ML-Based Pretest Probability Model of Obstructive CAD in Patients With Stable Chest Pain.

BACKGROUND: Updated pretest probability models (ESC2019, the PTP model supported by the European Soc...

Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction.

Physics-driven deep learning (PD-DL) models have proven to be a powerful approach for improved recon...

Using Deep learning to Predict Cardiovascular Magnetic Resonance Findings from Echocardiography Videos.

BACKGROUND: Echocardiography is the most common modality for assessing cardiac structure and functio...

Fully automated measurement of aortic pulse wave velocity from routine cardiac MRI studies.

INTRODUCTION: Aortic pulse wave velocity (PWV) is a prognostic biomarker for cardiovascular disease,...

Machine learning-based hemodynamics quantitative assessment of pulmonary circulation using computed tomographic pulmonary angiography.

BACKGROUND: Pulmonary hypertension (pH) is a malignant pulmonary circulation disease. Right heart ca...

Strategies for Treatment De-escalation in Metastatic Renal Cell Carcinoma.

Immune checkpoint inhibitors (ICIs) and targeted therapies have revolutionized the management of met...

Quantitative benchmarking of nuclear segmentation algorithms in multiplexed immunofluorescence imaging for translational studies.

Multiplexed imaging techniques require identifying different cell types in the tissue. To utilize th...

Artificial Intelligence for Assessment of Digital Mammography Positioning Reveals Persistent Challenges.

OBJECTIVE: Mammographic breast cancer detection depends on high-quality positioning, which is tradit...

Phantom-Based Ultrasound-ECG Deep Learning Framework for Prospective Cardiac Computed Tomography.

OBJECTIVE: We present the first multimodal deep learning framework combining ultrasound (US) and ele...

End-to-end 2D/3D registration from pre-operative MRI to intra-operative fluoroscopy for orthopedic procedures.

PURPOSE: Soft tissue pathologies and bone defects are not easily visible in intra-operative fluorosc...

Deploying a novel deep learning framework for segmentation of specific anatomical structures on cone-beam CT.

AIM: Cone-beam computed tomography (CBCT) imaging plays a crucial role in dentistry, with automatic ...

Using AI to triage patients without clinically significant prostate cancer using biparametric MRI and PSA.

OBJECTIVES: To train and evaluate the performance of a machine learning triaging tool that identifie...

The value of artificial intelligence in PSMA PET: a pathway to improved efficiency and results.

INTRODUCTION: This systematic review investigates the potential of artificial intelligence (AI) in i...

Brain Tumour Detection Using VGG-Based Feature Extraction With Modified DarkNet-53 Model.

The objective of AI research and development is to create intelligent systems capable of performing ...

Integrating Radiogenomics and Machine Learning in Musculoskeletal Oncology Care.

Musculoskeletal tumors present a diagnostic challenge due to their rarity, histological diversity, a...

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