کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4953426 1443010 2017 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A framework for analysis of linear ultrasound videos to detect fetal presentation and heartbeat
ترجمه فارسی عنوان
یک چارچوب برای تجزیه و تحلیل فیلم های سونوگرافی خطی برای تشخیص ارائه جنین و ضربان قلب
کلمات کلیدی
ویدئو اولتراسوند، ارائه جنین و ضربان قلب، فراگیری ماشین،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر گرافیک کامپیوتری و طراحی به کمک کامپیوتر
چکیده انگلیسی


- Standard obstetric ultrasound examination requires expert sonographers.
- A framework is proposed to detect fetal presentation & heartbeat, for novice users.
- This is based on predefined free-hand ultrasound videos of the maternal abdomen.

Confirmation of pregnancy viability (presence of fetal cardiac activity) and diagnosis of fetal presentation (head or buttock in the maternal pelvis) are the first essential components of ultrasound assessment in obstetrics. The former is useful in assessing the presence of an on-going pregnancy and the latter is essential for labour management. We propose an automated framework for detection of fetal presentation and heartbeat from a predefined free-hand ultrasound sweep of the maternal abdomen. Our method exploits the presence of key anatomical sonographic image patterns in carefully designed scanning protocols to develop, for the first time, an automated framework allowing novice sonographers to detect fetal breech presentation and heartbeat from an ultrasound sweep. The framework consists of a classification regime for a frame by frame categorization of each 2D slice of the video. The classification scores are then regularized through a conditional random field model, taking into account the temporal relationship between the video frames. Subsequently, if consecutive frames of the fetal heart are detected, a kernelized linear dynamical model is used to identify whether a heartbeat can be detected in the sequence. In a dataset of 323 predefined free-hand videos, covering the mother's abdomen in a straight sweep, the fetal skull, abdomen, and heart were detected with a mean classification accuracy of 83.4%. Furthermore, for the detection of the heartbeat an overall classification accuracy of 93.1% was achieved.

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ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Medical Image Analysis - Volume 37, April 2017, Pages 22-36
نویسندگان
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