Artificial Neural Network-Based System for PET Volume Segmentation
المؤلفون المشاركون
Zaidi, Habib
Amira, Abbes
Abbod, Maysam F.
Sharif, Mhd Saeed
المصدر
International Journal of Biomedical Imaging
العدد
المجلد 2010، العدد 2010 (31 ديسمبر/كانون الأول 2010)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2010-09-26
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
Tumour detection, classification, and quantification in positron emission tomography (PET) imaging at early stage of disease are important issues for clinical diagnosis, assessment of response to treatment, and radiotherapy planning.
Many techniques have been proposed for segmenting medical imaging data; however, some of the approaches have poor performance, large inaccuracy, and require substantial computation time for analysing large medical volumes.
Artificial intelligence (AI) approaches can provide improved accuracy and save decent amount of time.
Artificial neural networks (ANNs), as one of the best AI techniques, have the capability to classify and quantify precisely lesions and model the clinical evaluation for a specific problem.
This paper presents a novel application of ANNs in the wavelet domain for PET volume segmentation.
ANN performance evaluation using different training algorithms in both spatial and wavelet domains with a different number of neurons in the hidden layer is also presented.
The best number of neurons in the hidden layer is determined according to the experimental results, which is also stated Levenberg-Marquardt backpropagation training algorithm as the best training approach for the proposed application.
The proposed intelligent system results are compared with those obtained using conventional techniques including thresholding and clustering based approaches.
Experimental and Monte Carlo simulated PET phantom data sets and clinical PET volumes of nonsmall cell lung cancer patients were utilised to validate the proposed algorithm which has demonstrated promising results.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Sharif, Mhd Saeed& Abbod, Maysam F.& Amira, Abbes& Zaidi, Habib. 2010. Artificial Neural Network-Based System for PET Volume Segmentation. International Journal of Biomedical Imaging،Vol. 2010, no. 2010, pp.1-11.
https://search.emarefa.net/detail/BIM-446779
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Sharif, Mhd Saeed…[et al.]. Artificial Neural Network-Based System for PET Volume Segmentation. International Journal of Biomedical Imaging No. 2010 (2010), pp.1-11.
https://search.emarefa.net/detail/BIM-446779
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Sharif, Mhd Saeed& Abbod, Maysam F.& Amira, Abbes& Zaidi, Habib. Artificial Neural Network-Based System for PET Volume Segmentation. International Journal of Biomedical Imaging. 2010. Vol. 2010, no. 2010, pp.1-11.
https://search.emarefa.net/detail/BIM-446779
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-446779
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