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This paper is focused on digital image analysis of B-MODE ultrasound images. Our study is specialized in transcranial B-images in neurology. We have developed an algorithm in MATLAB which is used to finding echogenicity level in substantia nigra to detection of Parkinson's Disease. The algorithm was also contemporaneously tested and verified for nucleus raphe echogenicity analysis. In addition, we...
The paper is focused on image processing of B-images from diagnostic ultrasound, their processing and analysis with own developed algorithm based on binary thresholding which is useful for images in grayscale such as B-images. The presented algorithm has been created as MATLAB-based application and verified its function for 2 different structures displayed in midbrain - substantia nigra and raphe...
We developed an algorithm and simultaneously a computer program to analysis and evaluation of ultrasound B-images. Ultrasound B-imaging is one of mostly used displaying method in radiology. Our developed method and program use of the principle of B-imaging and displaying in grayscale according to pulse-echo approach principle. The program is focused on measurement echogenic area inside defined ROI...
The goal of this presented paper is to show and explain how to measure echogenicity level in B-MODE ultrasound images. We present a method which we use in practice in our developed application in MATLAB. The application is usable in medical practice to echogenicity analysis in B-images. The core of the application is based on echogenicity level analysis in selectable area of interest which can be...
This paper shows how to classify the medical ultrasound images by using artificial intelligence with experimental software with MATLAB. The main goal is a classification of ROI substantia nigra in midbrain. This classification of the images is useful to detection Parkinson's disease. This work is based on image processing and is realized with the help of artificial intelligence which has been experimentally...
This paper describes how to recognize substantia nigra (SN) area in ultrasound brain-stem images. The main goal is the classification of ROI SN in midbrain. The classification of images is useful to detection Parkinson's disease (PD), defects in SN. Work is based on image processing and is realized with the help of artificial neural networks and solve is realized with MATLAB, with Image Processing...
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