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Optical coherence tomography-enabled classification of the human venoatrial junction.
J Biomed Opt
January 2025
Columbia University, Department of Electrical Engineering, New York, United States.
Significance: Radiofrequency ablation to treat atrial fibrillation (AF) involves isolating the pulmonary vein from the left atria to prevent AF from occurring. However, creating ablation lesions within the pulmonary veins can cause adverse complications.
Aim: We propose automated classification algorithms to classify optical coherence tomography (OCT) volumes of human venoatrial junctions.
FMCW-based contactless heart rate monitoring.
Sci Rep
January 2025
College of Computer Science and Engineering, Northwest Normal University, Lanzhou, 730070, Gansu, China.
Heart disease is a significant global health issue. Traditional methods for heart rate monitoring typically require close physical contact, which limits the continuity and convenience of monitoring. To achieve real-time, non-contact heartbeat monitoring, researchers have introduced millimeter-wave radar technology.
View Article and Find Full Text PDFImage Guided Percutaneous Robotic Interventions for Solid Organs.
Tech Vasc Interv Radiol
December 2024
Department of Interventional Oncology, Miami Cancer Institute, Baptist Health South Florida, Miami, FL; Department of Interventional Radiology, Miami Cardiac and Vascular Institute, Baptist Health South Florida, Miami, FL; Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location VUmc, Cancer Center Amsterdam, AMS, The Netherlands. Electronic address:
Robotic systems for minimally invasive procedures, particularly in interventional oncology, have advanced significantly, especially for percutaneous interventions guided by CT, Cone-beam CT, and MRI. These systems, which include needle-guiding and needle-driving robots, enhance the precision of procedures like biopsy and tumor ablation. Needle-guiding robots plan and align the needle, while needle-driving robots autonomously advance it, improving needle placement accuracy, enabling out-of-plane insertion, and reducing radiation exposure.
View Article and Find Full Text PDFArtificial intelligence applied in identifying left ventricular walls in myocardial perfusion scintigraphy images: Pilot study.
PLoS One
January 2025
Electrical, Mechanical & Computer Engineering School, Federal University of Goias, Goiania, Brazil.
This paper proposes the use of artificial intelligence techniques, specifically the nnU-Net convolutional neural network, to improve the identification of left ventricular walls in images of myocardial perfusion scintigraphy, with the objective of improving the diagnosis and treatment of coronary artery disease. The methodology included data collection in a clinical environment, followed by data preparation and analysis using the 3D Slicer Platform for manual segmentation, and subsequently, the application of artificial intelligence models for automated segmentation, focusing on the efficiency of identifying the walls of the left ventricular. A total of 83 clinical routine exams were collected, each exam containing 50 slices, which is 4,150 images.
View Article and Find Full Text PDFAccurate Reconstruction of Right Heart Shape and Motion From Cine-MRI for Image-Driven Computational Hemodynamics.
Int J Numer Method Biomed Eng
January 2025
Dipartimento di Scienze Chirurgiche Odontostomatologiche e Materno-Infantili, Università di Verona, Verona, Italy.
Accurate reconstruction of the right heart geometry and motion from time-resolved medical images is crucial for diagnostic enhancement and computational analysis of cardiac blood dynamics. Commonly used segmentation and/or reconstruction techniques, exclusively relying on short-axis cine-MRI, lack precision in critical regions of the right heart, such as the ventricular base and the outflow tract, due to its unique morphology and motion. Furthermore, the reconstruction procedure is time-consuming and necessitates significant manual intervention for generating computational domains.
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