Radiology

Practical applications of AI in body imaging.

Artificial intelligence (AI) algorithms and deep learning continue to change the landscape of radiol...

Improving radiology reporting accuracy: use of GPT-4 to reduce errors in reports.

PURPOSE: Radiology reports are essential for communicating imaging findings to guide diagnosis and t...

Advances in Breast Cancer Detection: Biomarkers, Mechanisms, and Biosensor Technologies.

Breast cancer (BC), the most common cancer in women, remains a global health concern. According to t...

Diagnosis, clinical management, and emerging strategies for coronary artery disease in patients with cancer.

The intersection of cancer and coronary artery disease (CAD) presents complex clinical challenges re...

Constructing high-quality enhanced 4D-MRI with personalized modeling for liver cancer radiotherapy.

BACKGROUND: For magnetic resonance imaging (MRI), a short acquisition time and good image quality ar...

Generation of Fundus Fluorescein Angiography Videos for Health Care Data Sharing.

IMPORTANCE: Medical data sharing faces strict restrictions. Text-to-video generation shows potential...

Self-supervised learning for MRI reconstruction: a review and new perspective.

OBJECTIVE: To review the latest developments in self-supervised deep learning (DL) techniques for ma...

Morphology-based radiological-histological correlation on ultra-high-resolution energy-integrating detector CT using cadaveric human lungs: nodule and airway analysis.

OBJECTIVES: To evaluate the depiction capability of fine lung nodules and airways using high-resolut...

Shadows and reflections on radiology and artificial intelligence.

Deep Learning Model for Automated Segmentation of Orbital Structures in MRI Images.

BACKGROUND: Magnetic resonance imaging (MRI) is a crucial tool for visualizing orbital structures an...

Semi-automatic segmentation of elongated interventional instruments for online calibration of C-arm imaging system.

PURPOSE: The C-arm biplane imaging system, designed for cerebral angiography, detects pathologies li...

Deep Learning MRI Models for the Differential Diagnosis of Tumefactive Demyelination versus Wild-Type Glioblastoma.

BACKGROUND AND PURPOSE: Diagnosis of tumefactive demyelination can be challenging. The diagnosis of ...

Development and validation of a combined clinical and MRI-based biomarker model to differentiate mild cognitive impairment from mild Alzheimer's disease.

BACKGROUND: Two of the most common complaints seen in neurology clinics are Alzheimer's disease (AD)...

Multi-site validation of an interpretable model to analyze breast masses.

An external validation of IAIA-BL-a deep-learning based, inherently interpretable breast lesion mali...

Diagnostic Performance of Radiomics for Differentiating Intrahepatic Cholangiocarcinoma from Hepatocellular Carcinoma: A Systematic Review and Meta-analysis.

BACKGROUND: Differentiating intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC...

Integrating handheld ultrasound in rheumatology: A review of benefits and drawbacks.

Musculoskeletal ultrasound is a key tool in rheumatology for diagnosing and managing inflammatory ar...

Metasurface-enhanced terahertz imaging for glioblastoma in orthotopic xenograft mouse model combined with neural network decision making.

Terahertz (THz) optical sensing and imaging offer significant potential in a range of biological and...

Deep learning-based diffusion MRI tractography: Integrating spatial and anatomical information.

Diffusion MRI tractography technique enables non-invasive visualization of the white matter pathways...

Alterations in the functional MRI-based temporal brain organisation in individuals with obesity.

AIMS: Obesity is associated with functional alterations in the brain. Although spatial organisation ...

Streamlining the annotation process by radiologists of volumetric medical images with few-shot learning.

PURPOSE: Radiologist's manual annotations limit robust deep learning in volumetric medical imaging. ...

The evaluation of artificial intelligence in mammography-based breast cancer screening: Is breast-level analysis enough?

OBJECTIVES: To assess whether the diagnostic performance of a commercial artificial intelligence (AI...