کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6891003 1445223 2018 42 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Fully automatic cervical vertebrae segmentation framework for X-ray images
ترجمه فارسی عنوان
چارچوب تقسیم بندی مهر و موم شده کاملا خودکار برای تصاویر اشعه ایکس
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
چکیده انگلیسی
The cervical spine is a highly flexible anatomy and therefore vulnerable to injuries. Unfortunately, a large number of injuries in lateral cervical X-ray images remain undiagnosed due to human errors. Computer-aided injury detection has the potential to reduce the risk of misdiagnosis. Towards building an automatic injury detection system, in this paper, we propose a deep learning-based fully automatic framework for segmentation of cervical vertebrae in X-ray images. The framework first localizes the spinal region in the image using a deep fully convolutional neural network. Then vertebra centers are localized using a novel deep probabilistic spatial regression network. Finally, a novel shape-aware deep segmentation network is used to segment the vertebrae in the image. The framework can take an X-ray image and produce a vertebrae segmentation result without any manual intervention. Each block of the fully automatic framework has been trained on a set of 124 X-ray images and tested on another 172 images, all collected from real-life hospital emergency rooms. A Dice similarity coefficient of 0.84 and a shape error of 1.69 mm have been achieved.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Methods and Programs in Biomedicine - Volume 157, April 2018, Pages 95-111
نویسندگان
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