Extracting Cross-Sectional Clinical Images Based on Their Principal Axes of Inertia
المؤلفون المشاركون
Fan, Yuzhou
Djuric, Marija
Li, Zhiyu
Antonijevic, Djordje
Milenkovic, Petar
Sun, Yueyang
Li, Ruining
Fan, Yifang
Luo, Liangping
المصدر
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-12-19
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
Cross-sectional imaging is considered the gold standard in diagnosing a range of diseases.
However, despite its widespread use in clinical practice and research, no widely accepted method is available to reliably match cross-sectional planes in several consecutive scans.
This deficiency can impede comparison between cross-sectional images and ultimately lead to misdiagnosis.
Here, we propose and demonstrate a method for finding the same imaging plane in images obtained during separate scanning sessions.
Our method is based on the reconstruction of a “virtual organ” from which arbitrary cross-sectional images can be extracted, independent of the axis orientation in the original scan or cut; the key is to establish unique body coordinates of the organ from its principal axes of inertia.
To verify our method a series of tests were performed, and the same cross-sectional plane was successfully extracted.
This new approach offers clinicians access, after just a single scanning session, to the morphology and structure of a lesion through cross-sectional images reconstructed along arbitrary axes.
It also aids comparable detection of morphological and structural changes in the same imaging plane from scans of the same patient taken at different times—thus potentially reducing the misdiagnosis rate when cross-sectional images are interpreted.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Fan, Yuzhou& Luo, Liangping& Djuric, Marija& Li, Zhiyu& Antonijevic, Djordje& Milenkovic, Petar…[et al.]. 2017. Extracting Cross-Sectional Clinical Images Based on Their Principal Axes of Inertia. Scanning،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1197800
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Fan, Yuzhou…[et al.]. Extracting Cross-Sectional Clinical Images Based on Their Principal Axes of Inertia. Scanning No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1197800
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Fan, Yuzhou& Luo, Liangping& Djuric, Marija& Li, Zhiyu& Antonijevic, Djordje& Milenkovic, Petar…[et al.]. Extracting Cross-Sectional Clinical Images Based on Their Principal Axes of Inertia. Scanning. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1197800
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1197800
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