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Automatic Radiographic Position Recognition from Image Frequency and Intensity
المؤلفون المشاركون
Ren, Ning-ning
Ma, An-ran
Han, Li-bo
Sun, Yong
Shao, Yan
Qiu, Jian-feng
المصدر
Journal of Healthcare Engineering
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-09-17
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
Purpose.
With the development of digital X-ray imaging and processing methods, the categorization and analysis of massive digital radiographic images need to be automatically finished.
What is crucial in this processing is the automatic retrieval and recognition of radiographic position.
To address these concerns, we developed an automatic method to identify a patient’s position and body region using only frequency curve classification and gray matching.
Methods.
Our new method is combined with frequency analysis and gray image matching.
The radiographic position was determined from frequency similarity and amplitude classification.
The body region recognition was performed by image matching in the whole-body phantom image with prior knowledge of templates.
The whole-body phantom image was stitched by radiological images of different parts.
Results.
The proposed method can automatically retrieve and recognize the radiographic position and body region using frequency and intensity information.
It replaces 2D image retrieval with 1D frequency curve classification, with higher speed and accuracy up to 93.78%.
Conclusion.
The proposed method is able to outperform the digital X-ray image’s position recognition with a limited time cost and a simple algorithm.
The frequency information of radiography can make image classification quicker and more accurate.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Ren, Ning-ning& Ma, An-ran& Han, Li-bo& Sun, Yong& Shao, Yan& Qiu, Jian-feng. 2017. Automatic Radiographic Position Recognition from Image Frequency and Intensity. Journal of Healthcare Engineering،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1180870
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Ren, Ning-ning…[et al.]. Automatic Radiographic Position Recognition from Image Frequency and Intensity. Journal of Healthcare Engineering No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1180870
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Ren, Ning-ning& Ma, An-ran& Han, Li-bo& Sun, Yong& Shao, Yan& Qiu, Jian-feng. Automatic Radiographic Position Recognition from Image Frequency and Intensity. Journal of Healthcare Engineering. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1180870
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1180870
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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