کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4953467 1443014 2016 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Cardiac image modelling: Breadth and depth in heart disease
ترجمه فارسی عنوان
مدل سازی تصویر قلب: عرض و عمق در بیماری قلبی
کلمات کلیدی
مدل سازی محاسباتی، اطلس قلب، بیومکانیک،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر گرافیک کامپیوتری و طراحی به کمک کامپیوتر
چکیده انگلیسی


- Population-based large cohort studies give an unprecedented breadth to the quantification of population variation and disease development in cardiac performance.
- Biophysical properties of myocardial tissue in health and disease can be obtained by interpreting imaging data using computational modelling.
- Open benchmarks for algorithm comparison and validation, open sharing of data and algorithms, and demonstration of clinical efficacy in patient management and care are needed for future developments in this field.

With the advent of large-scale imaging studies and big health data, and the corresponding growth in analytics, machine learning and computational image analysis methods, there are now exciting opportunities for deepening our understanding of the mechanisms and characteristics of heart disease. Two emerging fields are computational analysis of cardiac remodelling (shape and motion changes due to disease) and computational analysis of physiology and mechanics to estimate biophysical properties from non-invasive imaging. Many large cohort studies now underway around the world have been specifically designed based on non-invasive imaging technologies in order to gain new information about the development of heart disease from asymptomatic to clinical manifestations. These give an unprecedented breadth to the quantification of population variation and disease development. Also, for the individual patient, it is now possible to determine biophysical properties of myocardial tissue in health and disease by interpreting detailed imaging data using computational modelling. For these population and patient-specific computational modelling methods to develop further, we need open benchmarks for algorithm comparison and validation, open sharing of data and algorithms, and demonstration of clinical efficacy in patient management and care. The combination of population and patient-specific modelling will give new insights into the mechanisms of cardiac disease, in particular the development of heart failure, congenital heart disease, myocardial infarction, contractile dysfunction and diastolic dysfunction.

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ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Medical Image Analysis - Volume 33, October 2016, Pages 38-43
نویسندگان
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