Publication

Geometric Aspects in 3D Biomedical Image Processing

Michaël Unser, Philippe Thévenaz
1998
Journal Articles

Abstract

We present some issues that arise when a geometric transformation is performed on an image or a volume. In particular, we illustrate the well-known problems of blocking, blurring, aliasing and ringing. Although the solution to these problems is trivial in an analog (optical) image processing system, their solution in a discrete (numeric) context is much more difficult. The modern trend of biomedical image processing is to fight these artifacts by using more sophisticated models that emphasize the quality of interpolation. For example, spline kernels offer excellent performances for a low computational cost; in addition, this compromise can be tuned by controlling the degree of the spline.

Official source

https://infoscience.epfl.ch/entities/publication/cf1e7307-b554-4ad7-80a2-999cd95d0901

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Michaël Unser, Philippe Thévenaz
1998
Journal Articles

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/cf1e7307-b554-4ad7-80a2-999cd95d0901

About this result

Related concepts (21)

Medical imaging

Medical imaging is the technique and process of imaging the interior of a body for clinical analysis and medical intervention, as well as visual representation of the function of some organs or tissues (physiology). Medical imaging seeks to reveal internal structures hidden by the skin and bones, as well as to diagnose and treat disease. Medical imaging also establishes a database of normal anatomy and physiology to make it possible to identify abnormalities.

Geometric transformation

In mathematics, a geometric transformation is any bijection of a set to itself (or to another such set) with some salient geometrical underpinning. More specifically, it is a function whose domain and range are sets of points — most often both or both — such that the function is bijective so that its inverse exists. The study of geometry may be approached by the study of these transformations. Geometric transformations can be classified by the dimension of their operand sets (thus distinguishing between, say, planar transformations and spatial transformations).

Image segmentation

In and computer vision, image segmentation is the process of partitioning a into multiple image segments, also known as image regions or image objects (sets of pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics.

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