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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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Ground-truth in a medical machine learning project

Objective, well prepared data is the basis in medical machine learning project. After all, a machine learning model trained on a very good data set produces very good results. This is obvious. But how demanding professional ground-truth preparation is we have found out only recently. In a project where we use machine learning algorithms. Ground-truth[...]
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