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| http://dx.doi.org/10.5114/aic.2023.124361 | DOI Listing |
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Deep learning in 3D cardiac reconstruction: a systematic review of methodologies and dataset.
Med Biol Eng Comput
January 2025
Department of Computer Science and Engineering, Shri Shankaracharya Institute of Professional Management and Technology, Raipur, (C.G.), India.
This study presents an advanced methodology for 3D heart reconstruction using a combination of deep learning models and computational techniques, addressing critical challenges in cardiac modeling and segmentation. A multi-dataset approach was employed, including data from the UK Biobank, MICCAI Multi-Modality Whole Heart Segmentation (MM-WHS) challenge, and clinical datasets of congenital heart disease. Preprocessing steps involved segmentation, intensity normalization, and mesh generation, while the reconstruction was performed using a blend of statistical shape modeling (SSM), graph convolutional networks (GCNs), and progressive GANs.
View Article and Find Full Text PDFRefining cardiac resynchronization therapy: a comprehensive review on the role of advanced multimodality imaging.
Front Cardiovasc Med
December 2024
Department of Cardiology, University of Medicine and Pharmacy of Craiova, Craiova, Romania.
Cardiac resynchronization therapy (CRT) offers significant benefits in symptom alleviation, reduction of rehospitalization rates, and overall survival of patients with heart failure (HF) with reduced ejection fraction (rEF). However, despite its proven efficacy, precisely identifying suitable CRT candidates remains a challenge, with a notable proportion of patients experiencing non-response. Accordingly, many attempts have been made to enhance patient selection, and to identify the best imaging parameters to predict the response and survival after CRT implantation.
View Article and Find Full Text PDFA domed window chamber for multi-modality optical imaging.
Biotechniques
January 2025
Biomedical Engineering, The University of Arizona, Tucson, AZ, USA.
Current dorsal skin flap window chambers with flat glass windows are compatible with optical coherence tomography (OCT) and multiphoton microscopy (MPM) imaging. However, light sheet fluorescence microscopy (LSFM) performs best with a cylindrical or spherical sample located between its two 90° objectives and when all sample materials have the same index of refraction (). A modified window chamber with a domed viewing window made from fluorinated ethylene propylene (FEP), with n similar to water and tissue, was designed.
View Article and Find Full Text PDFThe In-depth Comparative Analysis of Four Large Language AI Models for Risk Assessment and Information Retrieval from Multi-Modality Prostate Cancer Work-up Reports.
World J Mens Health
December 2024
Division of Urology, Department of Surgery, Far Eastern Memorial Hospital, New Taipei, Taiwan.
Purpose: Information retrieval (IR) and risk assessment (RA) from multi-modality imaging and pathology reports are critical to prostate cancer (PC) treatment. This study aims to evaluate the performance of four general-purpose large language model (LLMs) in IR and RA tasks.
Materials And Methods: We conducted a study using simulated text reports from computed tomography, magnetic resonance imaging, bone scans, and biopsy pathology on stage IV PC patients.
Selecting the optimal candidates for percutaneous mitral valvuloplasty using multi-modality imaging.
Eur Heart J Cardiovasc Imaging
December 2024
Division of Radiology, Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea.
Aims: This study compared echocardiography (echo) and cardiac computed tomography (CT) in measuring the Wilkins score and evaluated the potential added benefit of CT in predicting immediate percutaneous mitral valvuloplasty (PMV) outcomes in rheumatic mitral stenosis (MS) patients deemed eligible for PMV by echo.
Methods And Results: From a multicentre registry of 3,140 patients with at least moderate MS, we included 96 patients (age 56.4±11.
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