Comparison between classical and clustering segmentation techniques

المؤلف

Zanati, E. A.

المصدر

International Journal of Intelligent Computing and Information Sciences

العدد

المجلد 7، العدد 1 (31 يناير/كانون الثاني 2007)20ص.

الناشر

جامعة عين شمس كلية الحاسبات و المعلومات

تاريخ النشر

2007-01-31

دولة النشر

مصر

عدد الصفحات

20

التخصصات الرئيسية

تكنولوجيا المعلومات وعلم الحاسوب

الموضوعات

الملخص EN

In this paper, we compare the performance of key classical and clustering techniques for image segmentation when they are applied on medical and non medical data.

These methods are applied on two different sets: reference images (RI), for objective evaluation based on estimation of segmentation accuracy and time, and non reference images (NRI), for objective evaluation based on combined judgment of opinions of specialists.

A direct benefit of this study is being able to determine the most suitable segmentation techniques for given application medical images.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Zanati, E. A.. 2007. Comparison between classical and clustering segmentation techniques. International Journal of Intelligent Computing and Information Sciences،Vol. 7, no. 1.
https://search.emarefa.net/detail/BIM-285029

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Zanati, E. A.. Comparison between classical and clustering segmentation techniques. International Journal of Intelligent Computing and Information Sciences Vol. 7, no. 1 (Jan. 2007).
https://search.emarefa.net/detail/BIM-285029

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Zanati, E. A.. Comparison between classical and clustering segmentation techniques. International Journal of Intelligent Computing and Information Sciences. 2007. Vol. 7, no. 1.
https://search.emarefa.net/detail/BIM-285029

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-285029