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Visar resultat 1 - 5 av 53 avhandlingar som matchar ovanstående sökkriterier.
1. Methods for Reliable Image Registration : Algorithms, Distance Measures, and Representations
Sammanfattning : Much biomedical and medical research relies on the collection of ever-larger amounts of image data (both 2D images and 3D volumes, as well as time-series) and increasingly from multiple sources. Image registration, the process of finding correspondences between images based on the affinity of features of interest, is often required as a vital step towards the final analysis, which may consist of a comparison of images, measurement of movement, or fusion of complementary information. LÄS MER
2. Representation Learning and Information Fusion : Applications in Biomedical Image Processing
Sammanfattning : In recent years Machine Learning and in particular Deep Learning have excelled in object recognition and classification tasks in computer vision. As these methods extract features from the data itself by learning features that are relevant for a particular task, a key aspect of this remarkable success is the amount of data on which these methods train. LÄS MER
3. Combining Shape and Learning for Medical Image Analysis
Sammanfattning : Automatic methods with the ability to make accurate, fast and robust assessments of medical images are highly requested in medical research and clinical care. Excellent automatic algorithms are characterized by speed, allowing for scalability, and an accuracy comparable to an expert radiologist. LÄS MER
4. Image Filtering Methods for Biomedical Applications
Sammanfattning : Filtering is a key step in digital image processing and analysis. It is mainly used for amplification or attenuation of some frequencies depending on the nature of the application. Filtering can either be performed in the spatial domain or in a transformed domain. LÄS MER
5. Improving Multi-Atlas Segmentation Methods for Medical Images
Sammanfattning : Semantic segmentation of organs or tissues, i.e. delineating anatomically or physiologically meaningful boundaries, is an essential task in medical image analysis. One particular class of automatic segmentation algorithms has proved to excel at a diverse set of medical applications, namely multi-atlas segmentation. LÄS MER