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Automatic Anatomy Recognition and Registration: Medical Image Processing and Analysis - Couverture souple

Ba?c?, Ula?

 
9783838380148: Automatic Anatomy Recognition and Registration: Medical Image Processing and Analysis
Couverture souple
ISBN 10 : 3838380142 ISBN 13 : 9783838380148
Editeur : LAP LAMBERT Academic Publishing, 2010

Synopsis

This thesis tackles two major challenges in medical image analysis: image segmentation and registration. Specifically, we present a novel anatomy recognition algorithm for assisting the image segmentation task, and a novel image registration framework for accurately aligning images. Whilst the anatomy recognition study considers different clinical applications using MR (magnetic resonance) and CT (computed tomography) images, the image registration study uses MR and histological images. We have also developed a novel and effective method for registering histological images of a mouse brain in order to reconstruct the 3D volume. Experiments show that the choice of the reference slice has a significant impact on the quality of 3D reconstruction. Finally, since image intensity variations are inherent in MR images, and since the lack of a standard image intensity scale in MRI leads to many difficulties in tissue characterisability, image display, and analysis, including image segmentation and registration, we systematically investigated and evaluated the influence of intensity standardisation in automatic anatomy recognition and registration tasks using clinical MR images.

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Présentation de l'éditeur

This thesis tackles two major challenges in medical image analysis: image segmentation and registration. Specifically, we present a novel anatomy recognition algorithm for assisting the image segmentation task, and a novel image registration framework for accurately aligning images. Whilst the anatomy recognition study considers different clinical applications using MR (magnetic resonance) and CT (computed tomography) images, the image registration study uses MR and histological images. We have also developed a novel and effective method for registering histological images of a mouse brain in order to reconstruct the 3D volume. Experiments show that the choice of the reference slice has a significant impact on the quality of 3D reconstruction. Finally, since image intensity variations are inherent in MR images, and since the lack of a standard image intensity scale in MRI leads to many difficulties in tissue characterisability, image display, and analysis, including image segmentation and registration, we systematically investigated and evaluated the influence of intensity standardisation in automatic anatomy recognition and registration tasks using clinical MR images.

Biographie de l'auteur

Dr. Ba?c? received his BSc and MSc degrees from Bilkent and Koç Universities (2003 and 2005), and PhD from University of Nottingham (2010). He was a Visiting Research Fellow in MIPG of University of Pennsylvania in 2009. He received several awards including Best Paper in the IEEE Conf.SIU 2006, Marie Curie Fellowship, and NIH ISTP Fellowship.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2010
Langue
anglais
ISBN 10 
3838380142
ISBN 13 
9783838380148
Reliure
Broché
Nombre de pages
168
Coordonnées du fabricant
non disponible
Personne responsable
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