AIMC Topic: Aortic Diseases
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Utilizing Machine Learning Techniques to Predict Negative Remodeling in Uncomplicated Type B Intramural Hematoma.
Annals of vascular surgery
Mar 5, 2025
BACKGROUND: To evaluate the effectiveness of machine learning (ML) techniques in predicting negative remodeling in uncomplicated Stanford type B intramural hematoma (IMHB) during the acute phase.
CIS-UNet: Multi-class segmentation of the aorta in computed tomography angiography via context-aware shifted window self-attention.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Nov 19, 2024
Advancements in medical imaging and endovascular grafting have facilitated minimally invasive treatments for aortic diseases. Accurate 3D segmentation of the aorta and its branches is crucial for interventions, as inaccurate segmentation can lead to ...
Aorta Segmentation in 3D CT Images by Combining Image Processing and Machine Learning Techniques.
Cardiovascular engineering and technology
Feb 22, 2024
PURPOSE: Aorta segmentation is extremely useful in clinical practice, allowing the diagnosis of numerous pathologies, such as dissections, aneurysms and occlusive disease. In such cases, image segmentation is prerequisite for applying diagnostic algo...
Low-tube-voltage whole-body CT angiography with extremely low iodine dose: a comparison between hybrid-iterative reconstruction and deep-learning image-reconstruction algorithms.
Clinical radiology
Feb 15, 2024
AIM: To evaluate arterial enhancement, its depiction, and image quality in low-tube potential whole-body computed tomography (CT) angiography (CTA) with extremely low iodine dose and compare the results with those obtained by hybrid-iterative reconst...
Deep Learning-Based Analysis of Aortic Morphology From Three-Dimensional MRI.
Journal of magnetic resonance imaging : JMRI
Jan 12, 2024
BACKGROUND: Quantification of aortic morphology plays an important role in the evaluation and follow-up assessment of patients with aortic diseases, but often requires labor-intensive and operator-dependent measurements. Automatic solutions would hel...
Current Artificial Intelligence Based Chatbots May Produce Inaccurate and Potentially Harmful Information for Patients With Aortic Disease.
European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery
Nov 11, 2023
Transthoracic Aortic Clamp Technique for Port-Only Endoscopic Robotic Mitral Surgery.
Innovations (Philadelphia, Pa.)
May 25, 2023
OBJECTIVE: Many robotic mitral surgeons utilize right thoracotomy with transthoracic clamping of the aorta, while a smaller number employ a port-only endoscopic approach with endoaortic balloon occlusion of the aorta. We present our technique for a p...
Deep-learning image-reconstruction algorithm for dual-energy CT angiography with reduced iodine dose: preliminary results.
Clinical radiology
Nov 12, 2021
AIM: To evaluate the computed tomography (CT) attenuation values, background noise, arterial depiction, and image quality in whole-body dual-energy CT angiography (DECTA) at 40 keV with a reduced iodine dose using deep-learning image reconstruction (...
Prehospital triage of acute aortic syndrome using a machine learning algorithm.
The British journal of surgery
Feb 11, 2020
BACKGROUND: Acute aortic syndrome (AAS) comprises a complex and potentially fatal group of conditions requiring emergency specialist management. The aim of this study was to build a prediction algorithm to assist prehospital triage of AAS.
Artificial Intelligence in Aortic Surgery: The Rise of the Machine.
Seminars in thoracic and cardiovascular surgery
Jul 4, 2019
The first concept of Artificial Intelligence (AI) came into attention during 1920s and currently it is rapidly being integrated in our daily clinical practice. The use of AI has evolved from basic image-based analysis into complex decisions related t...
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