Matrix-free techniques for efficient image registration and their application to pulmonary image analysis

  • This PhD thesis presents a generic approach to more efficient image registration in a classical optimization-based framework. The calculation of the objective function derivatives is targeted as a whole, thereby fusing the computations for image transformation, interpolation and image similarity to one explicit, matrix-free expression. The employed concept reduces the auxiliary space requirements for derivative computation from linear to constant and greatly facilitates parallel execution. We study its usage both for affine-linear and deformable image registration algorithms designed for monomodal and multimodal problems. Additionally, implementations on alternative platforms such as graphics processing units or embedded digital signal processors are discussed. The practical value of the considered approach is illustrated on real-world applications from various areas of medical image computing. In particular, pulmonary image registration algorithms are studied for two use cases: computer assistance for lung cancer screening and oncological follow-up assessment, and quantitative analysis for chronic obstructive pulmonary disease. For both applications, efficient solutions are presented that combine state-of-the-art accuracy with clinically acceptable runtime and memory footprint. Our algorithms are extensively evaluated on three publicly available, expert-annotated data collections. The thesis is completed by a study of three further medical applications of image registration: alignment of positron emission tomography (PET) with computed tomography (CT) scans for joint radiological reading, registration of magnetic resonance and CT images in the context of deep brain stimulation, and real-time tracking of liver vessels in long ultrasound sequences for motion compensation. In all three applications, the proposed matrix-free calculation schemes contribute to moderate resource demands, which allow for unproblematic execution in a clinical environment.

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Publishing Institution:IRC-Library, Information Resource Center der Jacobs University Bremen
Granting Institution:Jacobs Univ.
Author:Jan Rune Rühaak
Referee:Horst Karl Hahn, Tobias Preußer, Harald Köstler
Advisor:Horst Karl Hahn
Persistent Identifier (URN):urn:nbn:de:gbv:579-opus-1007323
Document Type:PhD Thesis
Date of Successful Oral Defense:2017/06/23
Date of First Publication:2017/07/31
Academic Department:Computer Science & Electrical Engineering
PhD Degree:Computer Science
Focus Area:Mobility
Other Organisations Involved:Fraunhofer MEVIS
Call No:Thesis 2017/13

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