AIMC Topic: Tomography, X-Ray Computed

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Effect of Deep Learning Reconstruction on Evaluating Cervical Spinal Canal Stenosis With Computed Tomography.

Journal of computer assisted tomography
OBJECTIVE: Magnetic resonance imaging (MRI) is commonly used to evaluate cervical spinal canal stenosis; however, some patients are ineligible for MRI. We aimed to assess the effect of deep learning reconstruction (DLR) in evaluating cervical spinal ...

Improve the performance of CT-based pneumonia classification via source data reweighting.

Scientific reports
Pneumonia is a life-threatening disease. Computer tomography (CT) imaging is broadly used for diagnosing pneumonia. To assist radiologists in accurately and efficiently detecting pneumonia from CT scans, many deep learning methods have been developed...

Automatic Detection of Pancreatic Lesions and Main Pancreatic Duct Dilatation on Portal Venous CT Scans Using Deep Learning.

Investigative radiology
OBJECTIVES: This study proposes and evaluates a deep learning method to detect pancreatic neoplasms and to identify main pancreatic duct (MPD) dilatation on portal venous computed tomography scans.

Deep-learning based fast and accurate 3D CT deformable image registration in lung cancer.

Medical physics
BACKGROUND: Deformable Image Registration (DIR) is an essential technique required in many applications of radiation oncology. However, conventional DIR approaches typically take several minutes to register one pair of 3D CT images and the resulting ...

Deep Ensembles Are Robust to Occasional Catastrophic Failures of Individual DNNs for Organs Segmentations in CT Images.

Journal of digital imaging
Deep neural networks (DNNs) have recently showed remarkable performance in various computer vision tasks, including classification and segmentation of medical images. Deep ensembles (an aggregated prediction of multiple DNNs) were shown to improve a ...

Performance of an automated deep learning algorithm to identify hepatic steatosis within noncontrast computed tomography scans among people with and without HIV.

Pharmacoepidemiology and drug safety
PURPOSE: Hepatic steatosis (fatty liver disease) affects 25% of the world's population, particularly people with HIV (PWH). Pharmacoepidemiologic studies to identify medications associated with steatosis have not been conducted because methods to eva...

Joint liver and hepatic lesion segmentation in MRI using a hybrid CNN with transformer layers.

Computer methods and programs in biomedicine
UNLABELLED: Backgound and Objective: Deep learning-based segmentation of the liver and hepatic lesions therein steadily gains relevance in clinical practice due to the increasing incidence of liver cancer each year. Whereas various network variants w...

A CT-based deep learning system for automatic assessment of aortic root morphology for TAVI planning.

Computers in biology and medicine
Accurate planning of transcatheter aortic valve implantation (TAVI) is important to minimize complications, and it requires anatomic evaluation of the aortic root (AR), commonly performed through 3D computed tomography (CT) image analysis. Currently,...

Deep-learning CT reconstruction in clinical scans of the abdomen: a systematic review and meta-analysis.

Abdominal radiology (New York)
OBJECTIVE: To perform a systematic literature review and meta-analysis of the two most common commercially available deep-learning algorithms for CT.

Surgical Sealant with Integrated Shape-Morphing Dual Modality Ultrasound and Computed Tomography Sensors for Gastric Leak Detection.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Postoperative anastomotic leaks are the most feared complications after gastric surgery. For diagnostics clinicians mostly rely on clinical symptoms such as fever and tachycardia, often developing as a result of an already fully developed, i.e., symp...