Radiology

Brain Tumor Detection using Deep Learning Approach.

Early detection of brain tumor has an important role in further developing therapeutic outcomes, and...

New Horizons: Artificial Intelligence for Digital Breast Tomosynthesis.

The use of digital breast tomosynthesis (DBT) in breast cancer screening has become widely accepted,...

Deep Learning Based on Enhanced MRI T1 Imaging to Differentiate Small-cell and Non-small-cell Primary Lung Cancers in Patients with Brain Metastases.

OBJECTIVES: To differentiate the primary small-cell lung cancer (SCLC) and non-small-cell lung cance...

Deep learning image reconstruction for quality assessment of iodine concentration in computed tomography: A phantom study.

BACKGROUND: Recently, deep learning reconstruction (DLR) technology aiming to improve image quality ...

A Lightweight Low-dose PET Image Super-resolution Reconstruction Method based on Convolutional Neural Network.

BACKGROUND: PET imaging is one of the most widely used neurological disease screening and diagnosis ...

Review on Computer Aided Breast Cancer Detection and Diagnosis using Machine Learning Methods on Mammogram Image.

Machine Learning (ML) plays an essential part in the research area of medical image processing. The ...

Machine learning analysis of breast ultrasound to classify triple negative and HER2+ breast cancer subtypes.

OBJECTIVES: Early diagnosis of triple-negative (TN) and human epidermal growth factor receptor 2 pos...

Prediction of Axillary Lymph Node Metastatic Load of Breast Cancer Based on Ultrasound Deep Learning Radiomics Nomogram.

Axillary lymph node (ALN) metastatic load is very important in the diagnosis and treatment of breas...

FNSAM: Image super-resolution using a feedback network with self-attention mechanism.

BACKGROUND: High-resolution (HR) magnetic resonance imaging (MRI) provides rich pathological informa...

Robotics in Interventional Radiology: Review of Current and Future Applications.

This review is a brief overview of the current status and the potential role of robotics in interven...

Artificial intelligence in Nuclear Medicine Physics and Imaging.

No one can deny the significant impact of artificial intelligence (AI) on everyday life, especially ...

[[PET] 6. Overview of Clinical Applications of Artificial Intelligence in PET].

Performance of deep learning in classifying malignant primary and metastatic brain tumors using different MRI sequences: A medical analysis study.

BACKGROUND: Malignant Primary Brain Tumor (MPBT) and Metastatic Brain Tumor (MBT) are the most commo...

Clinical Importance of 3D Volography in Breast Imaging.

The clinical applications of the volography algorithm and concomitant refraction-corrected reflectio...

Usability and Acceptability of Social Robot Pets Among Community-Dwelling Veterans Living With Dementia and Their Caregivers.

Social robot pets promote engagement and psychosocial well-being among older adults, yet little is k...

Performance of a deep learning enhancement method applied to PET images acquired with a reduced acquisition time.

BACKGROUND: This study aims to evaluate the performance of a deep learning enhancement method in PET...

Cirq Robotic Assistance for Thoracolumbar Pedicle Screw Placement: Overcoming the Disadvantages of Minimally Invasive Spine Surgery.

INTRODUCTION: Various minimally invasive spine surgery (MISS) techniques have been developed with th...

Advancing Diabetic Retinopathy Diagnosis: Leveraging Optical Coherence Tomography Imaging with Convolutional Neural Networks.

Diabetic retinopathy (DR) is a vision-threatening complication of diabetes, necessitating early and ...

First Case Report Of Anca-Associated Vasculitis And Anthracosis Coexistence.

Anthracosis is a type of mild pneumoconiosis secondary to harmless carbon dust deposits. Although an...

[Ultrasound anatomy of masticatory muscles. (Experimental and clinical study)].

PURPOSE: To describe the ultrasound anatomy of the masticatory muscles based on a comparison of the ...

[A deep-learning model for the assessment of coronary heart disease and related risk factors via the evaluation of retinal fundus photographs].

To develop and validate a deep learning model based on fundus photos for the identification of coro...