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Compressed SENSE. Krótszy czas i wysoka jakość obrazowania

Geerts-Ossevoort Liesbeth, Weerdt Elwin de, Duijndam Adri, IJperen Gert van, Peeters Hans, Doneva Mariya, Huang Marco Nijenhuis Alan, Winiarczyk Piotr

Inżynier i Fizyk Medyczny

2019

Vol. 8, nr 2

89--94

Dzięki zastosowaniu techniki Compressed SENSE w wielu sekwencjach badania MRI, możemy je przyspieszyć nawet o 20-40%, a to bardzo dobra wiadomość także dla pacjentów.

Hydrogen interactions in Magnetic Resonance Imaging. Histogram-based Segmentation of Brain Tissues

Gułkowski S., Olchowik J. M.

Materials Science Poland

2006

Vol. 24, No. 4

1051--1056

Magnetic resonance imaging (MRI) is a very popular, non-invasive medical diagnostic technique providing images of the human body. The method, commonly used in clinics and hospitals all over the world, is based on the magnetic properties of hydrogen atom and its interactions with magnetic field. MR images show differences in water content and distribution in various body tissues. Even different tissues in the same organ, such as the gray and white matter in brain, can easily be distinguished. For a precise analysis of the images obtained in the result of MR examination, special computer applications are used. The paper presents the basis for the magnetic resonance imaging and description of the method of brain segmentation which could be a useful software tool in daily medical diagnosis practice.

Detecting pathologies in magnetic resonance images of brain

Sędziwy A.

Image Processing & Communications

2003

Vol. 9, no 1-2

53-62

This article contains the algorithm of processing the computer images obtained during magnetic resonance examination. The purpose of the algorithm is to search automatically for the pathologies presence in such images and to make the rough estimation of their size. It is accomplished by analyzing the axial symmetry of processed pictures. Described procedure applies also to the computer tomography data and may be extended by the functionality of the qualitative and quantitative description of detected pathologies.