Segmentation of Brains and Rocks from Tomographic Reconstructions

Research output: Book/ReportPh.D. thesisResearch

Standard

Segmentation of Brains and Rocks from Tomographic Reconstructions. / Hansen, Jacob Daniel Kirstejn.

Department of Computer Science, Faculty of Science, University of Copenhagen, 2018. 129 p.

Research output: Book/ReportPh.D. thesisResearch

Harvard

Hansen, JDK 2018, Segmentation of Brains and Rocks from Tomographic Reconstructions. Department of Computer Science, Faculty of Science, University of Copenhagen. <https://soeg.kb.dk/permalink/45KBDK_KGL/1pioq0f/alma99123666755905763>

APA

Hansen, J. D. K. (2018). Segmentation of Brains and Rocks from Tomographic Reconstructions. Department of Computer Science, Faculty of Science, University of Copenhagen. https://soeg.kb.dk/permalink/45KBDK_KGL/1pioq0f/alma99123666755905763

Vancouver

Hansen JDK. Segmentation of Brains and Rocks from Tomographic Reconstructions. Department of Computer Science, Faculty of Science, University of Copenhagen, 2018. 129 p.

Author

Hansen, Jacob Daniel Kirstejn. / Segmentation of Brains and Rocks from Tomographic Reconstructions. Department of Computer Science, Faculty of Science, University of Copenhagen, 2018. 129 p.

Bibtex

@phdthesis{79c2190ba2a8448c9911dd5b1c2cf6d7,
title = "Segmentation of Brains and Rocks from Tomographic Reconstructions",
abstract = "Segmentation is an indispensable initial step in image analysis and computer vision. New advanced scanners and large scale imaging facilities have spiked the interest of researchers across fields to investigate the internal structures of objects in a noninvasive manner. However, with new machines come new artefacts and challenges that need to be addressed before subsequent analysis can be conducted.This thesis presents six novel variational methods for the recovery of segments in tomographic reconstructions. Two primary types of volumetric datasets are used as target application; porous chalk rocks, from X-ray computerised microtomography (X-ray μCT) and rat cranial scans, acquired through magnetic resonance imaging (MRI). Several types of artefacts are addressed, with an emphasis on bias fieldsthat corrupts both acquisition modalities.",
author = "Hansen, {Jacob Daniel Kirstejn}",
year = "2018",
language = "English",
publisher = "Department of Computer Science, Faculty of Science, University of Copenhagen",

}

RIS

TY - BOOK

T1 - Segmentation of Brains and Rocks from Tomographic Reconstructions

AU - Hansen, Jacob Daniel Kirstejn

PY - 2018

Y1 - 2018

N2 - Segmentation is an indispensable initial step in image analysis and computer vision. New advanced scanners and large scale imaging facilities have spiked the interest of researchers across fields to investigate the internal structures of objects in a noninvasive manner. However, with new machines come new artefacts and challenges that need to be addressed before subsequent analysis can be conducted.This thesis presents six novel variational methods for the recovery of segments in tomographic reconstructions. Two primary types of volumetric datasets are used as target application; porous chalk rocks, from X-ray computerised microtomography (X-ray μCT) and rat cranial scans, acquired through magnetic resonance imaging (MRI). Several types of artefacts are addressed, with an emphasis on bias fieldsthat corrupts both acquisition modalities.

AB - Segmentation is an indispensable initial step in image analysis and computer vision. New advanced scanners and large scale imaging facilities have spiked the interest of researchers across fields to investigate the internal structures of objects in a noninvasive manner. However, with new machines come new artefacts and challenges that need to be addressed before subsequent analysis can be conducted.This thesis presents six novel variational methods for the recovery of segments in tomographic reconstructions. Two primary types of volumetric datasets are used as target application; porous chalk rocks, from X-ray computerised microtomography (X-ray μCT) and rat cranial scans, acquired through magnetic resonance imaging (MRI). Several types of artefacts are addressed, with an emphasis on bias fieldsthat corrupts both acquisition modalities.

UR - https://soeg.kb.dk/permalink/45KBDK_KGL/1pioq0f/alma99123666755905763

M3 - Ph.D. thesis

BT - Segmentation of Brains and Rocks from Tomographic Reconstructions

PB - Department of Computer Science, Faculty of Science, University of Copenhagen

ER -

ID: 248898390