The Ontario Uterine Fibroid Embolization Trial. Part 2. Uterine fibroid reduction and symptom relief after uterine artery embolization for fibroids [PDF]
, 2003 Gaylene Pron +5 more
openalex +1 more source
Peritoneal seeding of embolic beads after uterine artery embolization
Radiology Case Reports, 2023 Background: Incidental identification of peritoneal nodules during laparoscopy may present a diagnostic dilemma. The differential diagnosis includes a variety of benign and malignant entities such as peritoneal carcinomatosis.
Younes Jahangiri, MD +5 more
doaj
Automatic Detection of Pulmonary Embolism using Computational Intelligence [PDF]
arXiv, 2007 This article describes the implementation of a system designed to automatically detect the presence of pulmonary embolism in lung scans. These images are firstly segmented, before alignment and feature extraction using PCA. The neural network was trained using the Hybrid Monte Carlo method, resulting in a committee of 250 neural networks and good ...
arxiv
Ovarian Artery Embolization Supplementing Uterine Embolization for Leiomyomata [PDF]
, 2003 Mara M. Barth, James B. Spies
openalex +1 more source
Uterine artery embolization for the treatment of uterine fibroids [PDF]
, 2003 Scott Goodwin
openalex +1 more source
Journal of Interventional Medicine, 2019 Objective: This study aimed to investigate the clinical effects of abdominal aortic balloon occlusion followed by uterine artery embolization for the treatment of pernicious placenta previa complicated with placenta accreta during cesarean section ...
Yanli Wang +3 more
doaj
Pregnancy after fibroid uterine artery embolization—results from the Ontario Uterine Fibroid Embolization Trial [PDF]
, 2003 Gaylene Pron +5 more
openalex +1 more source
Prognostic factors in uterine artery embolization [PDF]
, 2003 Lisa Rahangdale +4 more
openalex +1 more source
Uterine Artery Embolization: State of the Art [PDF]
, 2004 Robert L. Worthington-Kirsch
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DCE-Qnet: Deep Network Quantification of Dynamic Contrast Enhanced (DCE) MRI [PDF]
arXivIntroduction: Quantification of dynamic contrast-enhanced (DCE)-MRI has the potential to provide valuable clinical information, but robust pharmacokinetic modeling remains a challenge for clinical adoption. Methods: A 7-layer neural network called DCE-Qnet was trained on simulated DCE-MRI signals derived from the Extended Tofts model with the Parker ...
arxiv