Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder
المؤلفون المشاركون
Zhao, Guangjun
Wang, Xuchu
Tan, Liwen
Niu, Yanmin
Zhang, Shao-Xiang
المصدر
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-01-26
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel).
Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain.
However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference.
In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations.
Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels.
Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies.
Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zhao, Guangjun& Wang, Xuchu& Niu, Yanmin& Tan, Liwen& Zhang, Shao-Xiang. 2016. Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder. BioMed Research International،Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1098079
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zhao, Guangjun…[et al.]. Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder. BioMed Research International No. 2016 (2016), pp.1-12.
https://search.emarefa.net/detail/BIM-1098079
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zhao, Guangjun& Wang, Xuchu& Niu, Yanmin& Tan, Liwen& Zhang, Shao-Xiang. Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder. BioMed Research International. 2016. Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1098079
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1098079
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