Abstract
Nowadays, many practical applications in the field of medical image processing require valid and reliable segmentation of images in the capacity of input data. Some of the commonly used imaging techniques are ultrasound, CT, and MRI. However, the main difference between the other medical imaging equipment and EchoCG is that it is safer, low cost, non-invasive and non-traumatic. Three-dimensional EchoCG is a non-invasive imaging modality that is complementary and supplementary to two-dimensional imaging and can be used to examine the cardiovascular function and anatomy in different medical settings. The challenging problems, presented by EchoCG image processing, such as speckle phenomena, noise, temporary non-stationarity of processes, unsharp boundaries, attenuation, etc. forced us to consider and compare existing methods and then to develop an innovative approach that can tackle the problems connected with clinical applications. Actual studies are related to the analysis and development of a cardiac parameters automatic detection system by EchoCG that will provide new data on the dynamics of changes in cardiac parameters and improve the accuracy and reliability of the diagnosis. Research study in image segmentation has highlighted the capabilities of image-based methods for medical applications. The focus of the research is both theoretical and practical aspects of the application of the methods. Some of the segmentation approaches can be interesting for the imaging and medical community. Performance evaluation is carried out by comparing the borders, obtained from the considered methods to those manually prescribed by a medical specialist. Promising results demonstrate the possibilities and the limitations of each technique for image segmentation problems. The developed approach allows: to eliminate errors in calculating the geometric parameters of the heart; perform the necessary conditions, such as speed, accuracy, reliability; build a master model that will be an indispensable assistant for operations on a beating heart.
Highlights
There are many different kinds of medical research studies and medical imaging modalities, closely related to image processing problems, such as angiography, echocardiography (EchoCG), cell magnetic resonance therapy and computed tomographic scanning
Image processing methods used in medical diagnostic belong to the static methods, i.e. working with each individual image and not taking into account the dynamics
The main hypothesis, considered in the study, is that the medical images of anatomical structures of the heart can be classified according to their geometrical properties and the properties of their environment; a segmentation algorithm can be defined for each class of objects, which allows getting a result that satisfies the subsequent usage in the scientific work
Summary
There are many different kinds of medical research studies and medical imaging modalities, closely related to image processing problems, such as angiography, echocardiography (EchoCG), cell magnetic resonance therapy and computed tomographic scanning. Today, these types of imaging modalities have been actively developing and they are the main diagnostic tools in their fields. Image processing methods used in medical diagnostic belong to the static methods, i.e. working with each individual image and not taking into account the dynamics.
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