Versatile Framework for Medical Image Processing and Analysis with Application to Automatic Bone Age Assessment
المؤلفون المشاركون
Zhao, Chen
Han, Jungang
Jia, Yang
Fan, Lianghui
Gou, Fan
المصدر
Journal of Electrical and Computer Engineering
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-12-31
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
Deep learning technique has made a tremendous impact on medical image processing and analysis.
Typically, the procedure of medical image processing and analysis via deep learning technique includes image segmentation, image enhancement, and classification or regression.
A challenge for supervised deep learning frequently mentioned is the lack of annotated training data.
In this paper, we aim to address the problems of training transferred deep neural networks with limited amount of annotated data.
We proposed a versatile framework for medical image processing and analysis via deep active learning technique.
The framework includes (1) applying deep active learning approach to segment specific regions of interest (RoIs) from raw medical image by using annotated data as few as possible; (2) generative adversarial Network is employed to enhance contrast, sharpness, and brightness of segmented RoIs; (3) Paced Transfer Learning (PTL) strategy which means fine-tuning layers in deep neural networks from top to bottom step by step to perform medical image classification or regression tasks.
In addition, in order to understand the necessity of deep-learning-based medical image processing tasks and provide clues for clinical usage, class active map (CAM) is employed in our framework to visualize the feature maps.
To illustrate the effectiveness of the proposed framework, we apply our framework to the bone age assessment (BAA) task using RSNA dataset and achieve the state-of-the-art performance.
Experimental results indicate that the proposed framework can be effectively applied to medical image analysis task.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zhao, Chen& Han, Jungang& Jia, Yang& Fan, Lianghui& Gou, Fan. 2018. Versatile Framework for Medical Image Processing and Analysis with Application to Automatic Bone Age Assessment. Journal of Electrical and Computer Engineering،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1184395
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zhao, Chen…[et al.]. Versatile Framework for Medical Image Processing and Analysis with Application to Automatic Bone Age Assessment. Journal of Electrical and Computer Engineering No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1184395
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zhao, Chen& Han, Jungang& Jia, Yang& Fan, Lianghui& Gou, Fan. Versatile Framework for Medical Image Processing and Analysis with Application to Automatic Bone Age Assessment. Journal of Electrical and Computer Engineering. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1184395
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1184395
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