Diagnostic Radiology

Diagnostic accuracy of artificial intelligence in detecting retinitis pigmentosa: A systematic review and meta-analysis.

Retinitis pigmentosa (RP) is often undetected in its early stages. Artificial intelligence (AI) has ...

Ethical Considerations for Artificial Intelligence in Medical Imaging: Data Collection, Development, and Evaluation.

The development of artificial intelligence (AI) within nuclear imaging involves several ethically fr...

Legal and ethical principles governing the use of artificial intelligence in radiology services in South Africa.

Artificial intelligence (AI) will drastically change the healthcare system. Radiology is one special...

Artificial intelligence in medical imaging is a tool for clinical routine and scientific discovery.

The emergence of powerful machine learning methodology together with an increasing amount of data co...

Self-supervised pre-training with contrastive and masked autoencoder methods for dealing with small datasets in deep learning for medical imaging.

Deep learning in medical imaging has the potential to minimize the risk of diagnostic errors, reduce...

Fusion of electronic health records and radiographic images for a multimodal deep learning prediction model of atypical femur fractures.

Atypical femur fractures (AFF) represent a very rare type of fracture that can be difficult to discr...

Understanding the factors influencing acceptability of AI in medical imaging domains among healthcare professionals: A scoping review.

BACKGROUND: Artificial intelligence (AI) technology has the potential to transform medical practice ...

Photon Absorption Remote Sensing Imaging of Breast Needle Core Biopsies Is Diagnostically Equivalent to Gold Standard H&E Histologic Assessment.

Photon absorption remote sensing (PARS) is a new laser-based microscope technique that permits cellu...

Best Practices for Artificial Intelligence and Machine Learning for Computer-Aided Diagnosis in Medical Imaging.

Healthcare Professional Association Agency in Preparing for Artificial Intelligence: A Multiple-Case Study of Radiation Medicine and Medical Imaging in the Canadian context.

As artificial intelligence (AI) is increasingly integrated in healthcare, it is incumbent on healthc...

Live-cell imaging in the deep learning era.

Live imaging is a powerful tool, enabling scientists to observe living organisms in real time. In pa...

Enhancing radiomics and Deep Learning systems through the standardization of medical imaging workflows.

Recent advances in computer-aided diagnosis, treatment response and prognosis in radiomics and deep ...

Assessing appropriate responses to ACR urologic imaging scenarios using ChatGPT and Bard.

Artificial intelligence (AI) has recently become a trending tool and topic regarding productivity es...

Exploring the performance of implicit neural representations for brain image registration.

Pairwise image registration is a necessary prerequisite for brain image comparison and data integrat...

Artificial Intelligence in Oncological Hybrid Imaging.

BACKGROUND:  Artificial intelligence (AI) applications have become increasingly relevant across a br...

The use of artificial intelligence tools in cancer detection compared to the traditional diagnostic imaging methods: An overview of the systematic reviews.

BACKGROUND AND PURPOSE: In comparison to conventional medical imaging diagnostic modalities, the aim...

Semi-TMS: an efficient regularization-oriented triple-teacher semi-supervised medical image segmentation model.

. Although convolutional neural networks (CNN) and Transformers have performed well in many medical ...

Black box no more: a scoping review of AI governance frameworks to guide procurement and adoption of AI in medical imaging and radiotherapy in the UK.

Technological advancements in computer science have started to bring artificial intelligence (AI) fr...

Evaluation of Proclarix in the diagnostic work-up of prostate cancer.

OBJECTIVES: The use of multiparametric magnetic resonance imaging (mpMRI) has been widely adopted in...

Physics-informed neural network for fast prediction of temperature distributions in cancerous breasts as a potential efficient portable AI-based diagnostic tool.

This work presents the development of a novel Physics-Informed Neural Network (PINN) method for fast...

Deep learning imaging reconstruction of reduced-dose 40 keV virtual monoenergetic imaging for early detection of colorectal cancer liver metastases.

OBJECTIVE: To explore whether reduced-dose (RD) gemstone spectral imaging (GSI) and deep learning im...