Enhanced Classification of Interstitial Lung Disease Patterns in HRCT Images Using Differential Lacunarity
المؤلفون المشاركون
Vasconcelos, Verónica
Barroso, João
Marques, Luis
Silvestre Silva, José
المصدر
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-12-22
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
The analysis and interpretation of high-resolution computed tomography (HRCT) images of the chest in the presence of interstitial lung disease (ILD) is a time-consuming task which requires experience.
In this paper, a computer-aided diagnosis (CAD) scheme is proposed to assist radiologists in the differentiation of lung patterns associated with ILD and healthy lung parenchyma.
Regions of interest were described by a set of texture attributes extracted using differential lacunarity (DLac) and classical methods of statistical texture analysis.
The proposed strategy to compute DLac allowed a multiscale texture analysis, while maintaining sensitivity to small details.
Support Vector Machines were employed to distinguish between lung patterns.
Training and model selection were performed over a stratified 10-fold cross-validation (CV).
Dimensional reduction was made based on stepwise regression (F-test, p value < 0.01) during CV.
An accuracy of 95.8 ± 2.2% in the differentiation of normal lung pattern from ILD patterns and an overall accuracy of 94.5 ± 2.1% in a multiclass scenario revealed the potential of the proposed CAD in clinical practice.
Experimental results showed that the performance of the CAD was improved by combining multiscale DLac with classical statistical texture analysis.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Vasconcelos, Verónica& Barroso, João& Marques, Luis& Silvestre Silva, José. 2015. Enhanced Classification of Interstitial Lung Disease Patterns in HRCT Images Using Differential Lacunarity. BioMed Research International،Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1056335
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Vasconcelos, Verónica…[et al.]. Enhanced Classification of Interstitial Lung Disease Patterns in HRCT Images Using Differential Lacunarity. BioMed Research International No. 2015 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1056335
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Vasconcelos, Verónica& Barroso, João& Marques, Luis& Silvestre Silva, José. Enhanced Classification of Interstitial Lung Disease Patterns in HRCT Images Using Differential Lacunarity. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1056335
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1056335
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر