AI Medical Compendium Topic:
Tomography, X-Ray Computed

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CT-based radiomics of machine-learning to screen high-risk individuals with kidney stones.

Urolithiasis
Screening high-risk populations is crucial for the prevention and treatment of kidney stones. Here, we employed radiomics to screen high-risk patients for kidney stones. A total of 513 independent kidneys from our hospital between 2020 and 2022 were ...

[Artificial intelligence in diagnostic radiology for dose management : Advances and perspectives using the example of computed tomography].

Radiologie (Heidelberg, Germany)
CLINICAL-METHODOLOGICAL PROBLEM: Imaging procedures employing ionizing radiation require compliance with European directives and national regulations in order to protect patients. Each exposure must be indicated, individually adapted, and documented....

A machine learning radiomics based on enhanced computed tomography to predict neoadjuvant immunotherapy for resectable esophageal squamous cell carcinoma.

Frontiers in immunology
BACKGROUND: Patients with resectable esophageal squamous cell carcinoma (ESCC) receiving neoadjuvant immunotherapy (NIT) display variable treatment responses. The purpose of this study is to establish and validate a radiomics based on enhanced comput...

Diagnostic test accuracy of externally validated convolutional neural network (CNN) artificial intelligence (AI) models for emergency head CT scans - A systematic review.

International journal of medical informatics
BACKGROUND: The surge in emergency head CT imaging and artificial intelligence (AI) advancements, especially deep learning (DL) and convolutional neural networks (CNN), have accelerated the development of computer-aided diagnosis (CADx) for emergency...

An emerging network for COVID-19 CT-scan classification using an ensemble deep transfer learning model.

Acta tropica
Over the past few years, the widespread outbreak of COVID-19 has caused the death of millions of people worldwide. Early diagnosis of the virus is essential to control its spread and provide timely treatment. Artificial intelligence methods are often...

DentalSegmentator: Robust open source deep learning-based CT and CBCT image segmentation.

Journal of dentistry
OBJECTIVES: Segmentation of anatomical structures on dento-maxillo-facial (DMF) computed tomography (CT) or cone beam computed tomography (CBCT) scans is increasingly needed in digital dentistry. The main aim of this research was to propose and evalu...

Streamlining Acute Abdominal Aortic Dissection Management-An AI-based CT Imaging Workflow.

Journal of imaging informatics in medicine
Life-threatening acute aortic dissection (AD) demands timely diagnosis for effective intervention. To streamline intrahospital workflows, automated detection of AD in abdominal computed tomography (CT) scans seems useful to assist humans. We aimed at...

Sex estimation from coxal bones using deep learning in a population balanced by sex and age.

International journal of legal medicine
In the field of forensic anthropology, researchers aim to identify anonymous human remains and determine the cause and circumstances of death from skeletonized human remains. Sex determination is a fundamental step of this procedure because it influe...

Enhancing trabecular CT scans based on deep learning with multi-strategy fusion.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Trabecular bone analysis plays a crucial role in understanding bone health and disease, with applications like osteoporosis diagnosis. This paper presents a comprehensive study on 3D trabecular computed tomography (CT) image restoration, addressing s...