BECT Spike Detection Algorithm Based on Optimal Template Matching and Morphological Feature Selection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems II: Express Briefs"
DOI: 10.1109/tcsii.2022.3151486
Abstract: Over 15% of children with epilepsy belong to benign childhood epilepsy with centro-temporal spikes (BECT), facing with educational difficulties. The accurate recognition of spikes in electroencephalogram (EEG) signals collected from BECT patients can help the… read more here.
Keywords: detection algorithm; template matching; spike detection; morphological feature ... See more keywords
Development and Comparison of Multimodal Models for Preoperative Prediction of Outcomes After Endovascular Aneurysm Repair
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Cardiovascular Medicine"
DOI: 10.3389/fcvm.2022.870132
Abstract: Objective The aim of this study was to develop and compare multimodal models for predicting outcomes after endovascular abdominal aortic aneurysm repair (EVAR) based on morphological, deep learning (DL), and radiomic features. Methods We retrospectively… read more here.
Keywords: multimodal models; development; model; feature model ... See more keywords
Corrigendum: Morphological feature and mapping inflammation in classified carotid plaques in symptomatic and asymptomatic patients: a hybrid 18F-FDG PET/MR study
Sign Up to like & getrecommendations! Published in 2023 at "Frontiers in Neuroscience"
DOI: 10.3389/fnins.2023.1209830
Abstract: [This corrects the article DOI: 10.3389/fnins.2023.1144248.]. read more here.
Keywords: feature mapping; classified carotid; inflammation classified; corrigendum morphological ... See more keywords
Differentiation Between Primary Central Nervous System Lymphoma and Atypical Glioblastoma Based on MRI Morphological Feature and Signal Intensity Ratio: A Retrospective Multicenter Study
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Oncology"
DOI: 10.3389/fonc.2022.811197
Abstract: Objectives To investigate the value of morphological feature and signal intensity ratio (SIR) derived from conventional magnetic resonance imaging (MRI) in distinguishing primary central nervous system lymphoma (PCNSL) from atypical glioblastoma (aGBM). Methods Pathology-confirmed PCNSLs… read more here.
Keywords: feature signal; auc acc; agbm; ratio ... See more keywords