Radiology

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Deep learning in sex estimation from a peripheral quantitative computed tomography scan of the fourth lumbar vertebra-a proof-of-concept study.

Sex estimation is a key element in the analysis of unknown skeletal remains. The vertebrae display c...

A deep learning-based fully automatic and clinical-ready framework for regional myocardial segmentation and myocardial ischemia evaluation.

Myocardial ischemia diagnosis with CT perfusion imaging (CTP) is important in coronary artery diseas...

Deep learning-based prediction of intra-cardiac blood flow in long-axis cine magnetic resonance imaging.

PURPOSE: We aimed to design and evaluate a deep learning-based method to automatically predict the t...

Reducing both radiation and contrast doses for overweight patients in coronary CT angiography with 80-kVp and deep learning image reconstruction.

PURPOSE: To investigate the use of an 80-kVp tube voltage combined with a deep learning image recons...

Identifying suicide attempts, ideation, and non-ideation in major depressive disorder from structural MRI data using deep learning.

The present study aims to identify suicide risks in major depressive disorders (MDD) patients from s...

Deep learning applications in osteoarthritis imaging.

Deep learning (DL) is one of the most exciting new areas in medical imaging. This article will provi...

LecturePlus: a learner-centered teaching method to promote deep learning.

A new teaching format, the LecturePlus, was formulated as a lecture followed by small-group learning...

HCTNet: A hybrid CNN-transformer network for breast ultrasound image segmentation.

Automatic breast ultrasound image segmentation helps radiologists to improve the accuracy of breast ...

Medical microrobots in reproductive medicine from the bench to the clinic.

Medical microrobotics is an emerging field that aims at non-invasive diagnosis and therapy inside th...

Rams, hounds and white boxes: Investigating human-AI collaboration protocols in medical diagnosis.

In this paper, we study human-AI collaboration protocols, a design-oriented construct aimed at estab...

Synthetic cranial MRI from 3D optical surface scans using deep learning for radiation therapy treatment planning.

BACKGROUND: Optical scanning technologies are increasingly being utilised to supplement treatment wo...

Multi-centre deep learning for placenta segmentation in obstetric ultrasound with multi-observer and cross-country generalization.

The placenta is crucial to fetal well-being and it plays a significant role in the pathogenesis of h...

Assessment of artificial intelligence (AI) reporting methodology in glioma MRI studies using the Checklist for AI in Medical Imaging (CLAIM).

PURPOSE: The Checklist for Artificial Intelligence in Medical Imaging (CLAIM) is a recently released...

Spatiotemporal analysis of speckle dynamics to track invisible needle in ultrasound sequences using convolutional neural networks: a phantom study.

PURPOSE: Accurate needle placement into the target point is critical for ultrasound interventions li...

Deep compressed sensing MRI via a gradient-enhanced fusion model.

BACKGROUND: Compressed sensing has been employed to accelerate magnetic resonance imaging by samplin...

Deep learning model integrating positron emission tomography and clinical data for prognosis prediction in non-small cell lung cancer patients.

BACKGROUND: Lung cancer is the leading cause of cancer-related deaths worldwide. The majority of lun...

Strategy for automatic ultrasound (US) probe positioning in robot-assisted ultrasound guided radiation therapy.

. As part of image-guided radiotherapy, ultrasound-guided radiotherapy is currently already in use a...

Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response.

Immunotherapy constitutes a paradigm shift in cancer treatment. Its FDA approval for several indicat...

Convolution Neural Networks and Self-Attention Learners for Alzheimer Dementia Diagnosis from Brain MRI.

Alzheimer's disease (AD) is the most common form of dementia. Computer-aided diagnosis (CAD) can hel...

A Review of Fusion Methods for Omics and Imaging Data.

The development of omics data and biomedical images has greatly advanced the progress of precision m...

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