medical image segmentation ai

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Automated Medical Image Analysis using AI: The Why, The How, and The What

We have been witnessing an unprecedented level of success achieved by the artificial intelligence (AI)-powered techniques in virtually all fields of science and industry, with medical image analysis not being an exception. Thanks to the availability of high-performance hardware and a variety of software tools, benefiting from the recent advances in classical machine leaning and[...]
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The road to perfection in medical image segmentation

In our previous posts so far we have covered the topic of the use of 3D modeling and medical image segmentation in cardiology.  We believe that showing our experience with these processes, presenting examples of application of 3D modeling and 3D printing in the cardiovascular field and a brief historical outline of medical image processing have helped to illustrate the enormous possibilities hidden within[...]
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3D medical image processing in cardiology

The previous post dealt with the topic of medical image segmentation as a method for preparing neural network learning data. However, the 3D medical image processing cardiovascular models prepared via the segmentation process have much wider applications.  The revolution in 3D medical image processing  It can be seen, that in recent years, advances in technology, 3D printing and[...]
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Medical image segmentation as a method for the preparation of learning data

Medical image segmentation is a seemingly a simple process. A number of factors contribute to achieving high quality end results, including proper preparation of medical input data for segmentation. In this post – as announced in the previous article – we will focus on the preparation of input data, i.e. medical image data for medical[...]
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Medical image segmentation as an advancement in medical imaging

It is hard to believe that we have been developing solutions related to the analysis of medical images for over 15 years. Rapid technological development has resulted in an increase in the quality of medical imaging methods and, consequently, in the diagnostic value of commonly performed imaging studies. Its natural consequence is the analysis and[...]
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