Automatic classification of thermal patterns in diabetic foot based on morphological pattern spectrum

被引：33

作者：

Hernandez-Contreras, D. ^{[1
]}

Peregrina-Barreto, H. ^{[1
]}

Rangel-Magdaleno, J. ^{[1
]}

Ramirez-Cortes, J. ^{[1
]}

Renero-Carrillo, F. ^{[1
]}

机构：

[1] Natl Inst Astrophys Opt & Elect, Puebla, Mexico

来源：

INFRARED PHYSICS & TECHNOLOGY | 2015年 / 73卷

关键词：

Thermography; Artificial neural network; Pattern spectrum; Diabetes mellitus; Diabetic foot; HIGH-RISK; THERMOGRAPHY;

D O I：

10.1016/j.infrared.2015.09.022

中图分类号：

TH7 [仪器、仪表];

学科分类号：

0804 ; 080401 ; 081102 ;

摘要：

This paper presents a novel approach to characterize and identify patterns of temperature in thermographic images of the human foot plant in support of early diagnosis and follow-up of diabetic patients. Composed feature vectors based on 3D morphological pattern spectrum (pecstrum) and relative position, allow the system to quantitatively characterize and discriminate non-diabetic (control) and diabetic (DM) groups. Non-linear classification using neural networks is used for that purpose. A classification rate of 9433% in average was obtained with the composed feature extraction process proposed in this paper. Performance evaluation and obtained results are presented. (C) 2015 Elsevier B.V. All rights reserved.

引用

页码：149 / 157

页数：9

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