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Segmentation of radiology images using pulse-coupled neural networks / Amr Hefny Muhammad ; Supervised Laila Fahmi , Amr A. Badr

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Amr Hefny Muhammad , 2011Description: 87 P. : facsimiles ; 25cmOther title:
  • تقسيم الصور الإشعاعية بإستخدام خوارزمي النبضة المتزاوجة للشبكات العصبية [Added title page title]
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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Science - Department of Mathematics Summary: This research develops an automated method for segmenting Magnetic Resonance (MR) brain images using Pulse Coupled Neural Networks (PCNN). MR brain image segmentation has proven difficult, primarily due to scanning artifacts such as interscan and intrascan intensity inhomogeneities. The method developed and presented here a PCNN to segment MR brain images after smooth it using PCNN it self and then detect brain tumors by comparing region properties by tumor properties
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Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.12.17.M.Sc.2011.Am.S (Browse shelf(Opens below)) Not for loan 01010110056613000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.12.17.M.Sc.2011.Am.S (Browse shelf(Opens below)) 56613.CD Not for loan 01020110056613000

Thesis (M.Sc.) - Cairo University - Faculty of Science - Department of Mathematics

This research develops an automated method for segmenting Magnetic Resonance (MR) brain images using Pulse Coupled Neural Networks (PCNN). MR brain image segmentation has proven difficult, primarily due to scanning artifacts such as interscan and intrascan intensity inhomogeneities. The method developed and presented here a PCNN to segment MR brain images after smooth it using PCNN it self and then detect brain tumors by comparing region properties by tumor properties

Issued also as CD

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