title: Residual stenosis estimation of arteriovenous grafts using a dual-channel phonoangiography with fractional-order features.
abstract: The residual stenosis estimation of an arteriovenous shunt is a valuable for evaluating outcomes of percutaneous transluminal angioplasty (PTA) treatment and surgical revision. This paper proposes a dual-channel phonoangiography (PCG) with fractional-order features to estimate the residual of stenosis estimation of arteriovenous shunt. The auscultation technique provides a noninvasive tool to monitor the degrees of arteriovenous grafts (AVGs). Then, support methods, such as the Burg autoregressive (AR) method and self-synchronization error formulation (SSEF), are used to extract fractional-order features between the loop site (L-site) and venous anastomosis site (V-site). Using 2-D patterns (nonlinear mapping), a generalized regression neural network (GRNN) is designed as a nonlinear estimate model to indicate the outcome of surgical revision or AVG stenosis upon routine monthly examinations. For 42 long-term follow-up patients, the results of examination show the proposed GRNN-based screening model efficiently estimates residual stenosis.
authors.forename: Yi-Chun
authors.initials: YC
authors.lastname: Du
authors.forename: Wei-Ling
authors.initials: WL
authors.lastname: Chen
authors.forename: Chia-Hung
authors.initials: CH
authors.lastname: Lin
authors.forename: Chung-Dann
authors.initials: CD
authors.lastname: Kan
authors.forename: Ming-Jui
authors.initials: MJ
authors.lastname: Wu
mesh_terms: D000368:Aged; D000792:Angiography / Q000379:methods*; D017130:Angioplasty / Q000009:adverse effects; D001166:Arteriovenous Shunt, Surgical; D001314:Auscultation / Q000379:methods*; D003251:Constriction, Pathologic / Q000175:diagnosis*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D016571:Neural Networks, Computer; D012815:Signal Processing, Computer-Assisted