AIMC Topic: Tomography, X-Ray Computed

Clear Filters Showing 2241 to 2250 of 5128 articles

Development and validation of chest CT-based imaging biomarkers for early stage COVID-19 screening.

Frontiers in public health
Coronavirus Disease 2019 (COVID-19) is currently a global pandemic, and early screening is one of the key factors for COVID-19 control and treatment. Here, we developed and validated chest CT-based imaging biomarkers for COVID-19 patient screening fr...

Machine Learning for Adrenal Gland Segmentation and Classification of Normal and Adrenal Masses at CT.

Radiology
Background Adrenal masses are common, but radiology reporting and recommendations for management can be variable. Purpose To create a machine learning algorithm to segment adrenal glands on contrast-enhanced CT images and classify glands as normal or...

Convolutional bi-directional learning and spatial enhanced attentions for lung tumor segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Accurate lung tumor segmentation from computed tomography (CT) is complex due to variations in tumor sizes, shapes, patterns and growing locations. Learning semantic and spatial relations between different feature channels, ...

Present status and future directions: Imaging techniques for the detection of periapical lesions.

International endodontic journal
Diagnosing and treating apical periodontitis (AP) in an attempt to preserve the natural dentition, and to prevent the direct and indirect systemic effects of this condition, is the major goal in endodontics. Considering that AP is frequently asymptom...

Characterizing Subjects Exposed to Humidifier Disinfectants Using Computed-Tomography-Based Latent Traits: A Deep Learning Approach.

International journal of environmental research and public health
Around nine million people have been exposed to toxic humidifier disinfectants (HDs) in Korea. HD exposure may lead to HD-associated lung injuries (HDLI). However, many people who have claimed that they experienced HD exposure were not diagnosed with...

Label-free intraoperative histology of bone tissue via deep-learning-assisted ultraviolet photoacoustic microscopy.

Nature biomedical engineering
Obtaining frozen sections of bone tissue for intraoperative examination is challenging. To identify the bony edge of resection, orthopaedic oncologists therefore rely on pre-operative X-ray computed tomography or magnetic resonance imaging. However, ...

Deep learning image reconstruction to improve accuracy of iodine quantification and image quality in dual-energy CT of the abdomen: a phantom and clinical study.

European radiology
OBJECTIVES: To investigate the effect of deep learning image reconstruction (DLIR) on the accuracy of iodine quantification and image quality of dual-energy CT (DECT) compared to that of other reconstruction algorithms in a phantom experiment and an ...

Leveraging Artificial Intelligence to Enhance Peer Review: Missed Liver Lesions on Computed Tomographic Pulmonary Angiography.

Journal of the American College of Radiology : JACR
PURPOSE: The aim of this study was to use artificial intelligence (AI) to facilitate peer review for detection of missed suspicious liver lesions (SLLs) on CT pulmonary angiographic (CTPA) examinations.