Development of a Stand-Alone Independent Graphical User Interface for Neurological Disease Prediction with Automated Extraction and Segmentation of Gray and White Matter in Brain MRI Images
المؤلفون المشاركون
Goyal, Ayush
Tirumalasetty, Sunayana
Hossain, Gahangir
Challoo, Rajab
Arya, Manish
Agrawal, Rajeev
Agrawal, Deepak
المصدر
Journal of Healthcare Engineering
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-21، 21ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-02-14
دولة النشر
مصر
عدد الصفحات
21
التخصصات الرئيسية
الملخص EN
This research presents an independent stand-alone graphical computational tool which functions as a neurological disease prediction framework for diagnosis of neurological disorders to assist neurologists or researchers in the field to perform automatic segmentation of gray and white matter regions in brain MRI images.
The tool was built in collaboration with neurologists and neurosurgeons and many of the features are based on their feedback.
This tool provides the user automatized functionality to perform automatic segmentation and extract the gray and white matter regions of patient brain image data using an algorithm called adapted fuzzy c-means (FCM) membership-based clustering with preprocessing using the elliptical Hough transform and postprocessing using connected region analysis.
Dice coefficients for several patient brain MRI images were calculated to measure the similarity between the manual tracings by experts and automatic segmentations obtained in this research.
The average Dice coefficients are 0.86 for gray matter, 0.88 for white matter, and 0.87 for total cortical matter.
Dice coefficients of the proposed algorithm were also the highest when compared with previously published standard state-of-the-art brain MRI segmentation algorithms in terms of accuracy in segmenting the gray matter, white matter, and total cortical matter.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Goyal, Ayush& Tirumalasetty, Sunayana& Hossain, Gahangir& Challoo, Rajab& Arya, Manish& Agrawal, Rajeev…[et al.]. 2019. Development of a Stand-Alone Independent Graphical User Interface for Neurological Disease Prediction with Automated Extraction and Segmentation of Gray and White Matter in Brain MRI Images. Journal of Healthcare Engineering،Vol. 2019, no. 2019, pp.1-21.
https://search.emarefa.net/detail/BIM-1175481
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Goyal, Ayush…[et al.]. Development of a Stand-Alone Independent Graphical User Interface for Neurological Disease Prediction with Automated Extraction and Segmentation of Gray and White Matter in Brain MRI Images. Journal of Healthcare Engineering No. 2019 (2019), pp.1-21.
https://search.emarefa.net/detail/BIM-1175481
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Goyal, Ayush& Tirumalasetty, Sunayana& Hossain, Gahangir& Challoo, Rajab& Arya, Manish& Agrawal, Rajeev…[et al.]. Development of a Stand-Alone Independent Graphical User Interface for Neurological Disease Prediction with Automated Extraction and Segmentation of Gray and White Matter in Brain MRI Images. Journal of Healthcare Engineering. 2019. Vol. 2019, no. 2019, pp.1-21.
https://search.emarefa.net/detail/BIM-1175481
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1175481
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