Titlebook: Introduction to Medical Image Analysis; Rasmus R. Paulsen,Thomas B. Moeslund Textbook 2020 Springer Nature Switzerland AG 2020 Medical Ima

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Color Images,tandard red, green, blue (RGB) representation is described together with less used but very important color spaces like the hue, saturation, and value (HSV) color space. Finally, it is described how thresholding can be used in color images.

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Pixel Classification,e liver in a computed tomography image. One commonly used step is pixel classification where each pixel is assigned a class-based purely on its value and independently of the pixel neighbors. In this chapter, we introduce basic pixel classification approaches like minimum distance classification and

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Geometric Transformations,is chapter, we start by covering affine transformation, including translation, scaling, rotation, and shearing. It is described how a transformation can be performed using matrices and how inverse mapping is used with bilinear interpolation to avoid sampling artifacts. Finally, some non-linear trans

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Line and Path Detection,tures. The Hough transform is a highly effective algorithm for detecting straight lines in images and is the topic of the first part of the chapter. In the second part, a method for tracing paths in images is presented. The algorithm is very fast and is based on the algorithmic approach called dynam

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Rasmus R. Paulsen,Thomas B. Moeslund ist. Das Empowerment Transformation Model visualisiert dabei die unterschiedlichen Komponenten und Schritte auf dem Weg zum Empowermentziel. Es geht um die Formulierung eines Anliegens, wo mit welchem Ziel Empowerment erreicht werden soll. Die Auseinandersetzung mit systemischen Fragen – vor allem

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Neighborhood Processing,on and convolution operations are described and used with different filter kernels as, for example, the Prewitt edge filter. Finally, more advanced filtering approaches like template matching and gradient filters are described.

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