AI Medical Compendium Topic

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Tomography, X-Ray Computed

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SPE-YOLO: A deep learning model focusing on small pulmonary embolism detection.

Computers in biology and medicine
OBJECTIVES: By developing the deep learning model SPE-YOLO, the detection of small pulmonary embolism has been improved, leading to more accurate identification of this condition. This advancement aims to better serve medical diagnosis and treatment.

Predicting craniofacial fibrous dysplasia growth status: an exploratory study of a hybrid radiomics and deep learning model based on computed tomography images.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: This study aimed to develop 3 models based on computed tomography (CT) images of patients with craniofacial fibrous dysplasia (CFD): a radiomics model (Model Rad), a deep learning (DL) model (Model DL), and a hybrid radiomics and DL model ...

Diagnostic performance of an artificial intelligence model for the detection of pneumothorax at chest X-ray.

Clinical imaging
PURPOSE: Pneumothorax (PTX) is a common clinical urgency, its diagnosis is usually performed on chest radiography (CXR), and it presents a setting where artificial intelligence (AI) methods could find terrain in aiding radiologists in facing increasi...

Generalizable self-supervised learning for brain CTA in acute stroke.

Computers in biology and medicine
Acute stroke management involves rapid and accurate interpretation of CTA imaging data. However, generalizable models for multiple acute stroke tasks able to learn from unlabeled data do not exist. We propose a linear probed self-supervised contrasti...

Deep learning prediction of scenario doses for direct plan robustness evaluations in IMPT for head-and-neck.

Physics in medicine and biology
. Intensity modulated proton therapy (IMPT) is susceptible to uncertainties in patient setup and proton range. Robust optimization is employed in IMPT treatment planning to ensure sufficient coverage of the clinical target volume (CTV) in predefined ...

Prediction of Bone Mineral Density based on Computer Tomography Images Using Deep Learning Model.

Gerontology
INTRODUCTION: The problem of population aging is intensifying worldwide. Osteoporosis has become an important cause affecting the health status of older populations. However, the diagnosis of osteoporosis and people's understanding of it are seriousl...

Evaluating the effectiveness of AI-powered UrologiQ's in accurately measuring kidney stone volume in urolithiasis patients.

Urolithiasis
Kidney stones and urolithiasis are kidney diseases that have a significant impact on health and well-being, and their incidence is increasing annually owing to factors such as age, sex, ethnicity, and geographical location. Accurate identification an...

Deep learning segmentation-based bone removal from computed tomography of the brain improves subdural hematoma detection.

Journal of neuroradiology = Journal de neuroradiologie
PURPOSE: Timely identification of intracranial blood products is clinically impactful, however the detection of subdural hematoma (SDH) on non-contrast CT scans of the head (NCCTH) is challenging given interference from the adjacent calvarium. This w...

Large-scale multi-center CT and MRI segmentation of pancreas with deep learning.

Medical image analysis
Automated volumetric segmentation of the pancreas on cross-sectional imaging is needed for diagnosis and follow-up of pancreatic diseases. While CT-based pancreatic segmentation is more established, MRI-based segmentation methods are understudied, la...