Classification of Pulmonary Nodules by Using Hybrid Features

المؤلفون المشاركون

Tartar, Ahmet
Akan, Aydin
Kilic, Niyazi

المصدر

Computational and Mathematical Methods in Medicine

العدد

المجلد 2013، العدد 2013 (31 ديسمبر/كانون الأول 2013)، ص ص. 1-11، 11ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2013-06-25

دولة النشر

مصر

عدد الصفحات

11

التخصصات الرئيسية

الطب البشري

الملخص EN

Early detection of pulmonary nodules is extremely important for the diagnosis and treatment of lung cancer.

In this study, a new classification approach for pulmonary nodules from CT imagery is presented by using hybrid features.

Four different methods are introduced for the proposed system.

The overall detection performance is evaluated using various classifiers.

The results are compared to similar techniques in the literature by using standard measures.

The proposed approach with the hybrid features results in 90.7% classification accuracy (89.6% sensitivity and 87.5% specificity).

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Tartar, Ahmet& Kilic, Niyazi& Akan, Aydin. 2013. Classification of Pulmonary Nodules by Using Hybrid Features. Computational and Mathematical Methods in Medicine،Vol. 2013, no. 2013, pp.1-11.
https://search.emarefa.net/detail/BIM-449602

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Tartar, Ahmet…[et al.]. Classification of Pulmonary Nodules by Using Hybrid Features. Computational and Mathematical Methods in Medicine No. 2013 (2013), pp.1-11.
https://search.emarefa.net/detail/BIM-449602

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Tartar, Ahmet& Kilic, Niyazi& Akan, Aydin. Classification of Pulmonary Nodules by Using Hybrid Features. Computational and Mathematical Methods in Medicine. 2013. Vol. 2013, no. 2013, pp.1-11.
https://search.emarefa.net/detail/BIM-449602

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-449602