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Digital processing of neurologic images.

Kelm, Zachary Samuel.

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Digital processing of neurologic images.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Digital processing of neurologic images./
Author:	Kelm, Zachary Samuel.
Description:	103 p.
Notes:	Source: Dissertation Abstracts International, Volume: 76-07(E), Section: B.
Contained By:	Dissertation Abstracts International76-07B(E).
Subject:	Medical imaging. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3683333
ISBN:	9781321574388

Digital processing of neurologic images.
Kelm, Zachary Samuel.

Digital processing of neurologic images. - 103 p.

Source: Dissertation Abstracts International, Volume: 76-07(E), Section: B.

Thesis (Ph.D.)--College of Medicine - Mayo Clinic, 2015.

This item is not available from ProQuest Dissertations & Theses.

Digital processing can be used to greatly enhance the utility of medical images. This document includes analysis and development of multiple digital image processing methods, both individually and in aggregate, for neurologic image applications. We investigated parameter optimization and novel extension of the nonlocal means denoising algorithm, showing that using a very small search window can result in increased denoising performance with proper adjustment of the other parameters, and that the nonlocal property can be exploited to use thick slice reconstructions in denoising thin slice reconstructions. After developing a whole brain segmentation algorithm for a valuable set of magnetic resonance (MR) exams of multiple sclerosis patients with biopsy-proven immunopattern classifications, we present analysis showing no significant tissue- and acquisition-specific MR signal intensity differences between the immunopatterns. Finally, we discovered clinically significant differences in measurement output from FDA-approved software used for computing cerebral blood volume maps from dynamic susceptibility contrast MR images. The potential clinical impact of these differences is shown to be disagreement between the software 20-50% of the time regarding classification of post-radiation treatment glioblastoma multiforme patients as having progressing or pseudoprogressing tumor. Additionally, the results indicate that 3.0 T MR acquisitions provide more useful perfusion information for identification of tumor pseudoprogression than 1.5 T acquisitions.

ISBN: 9781321574388Subjects--Topical Terms:

3172799
Medical imaging.

Digital processing of neurologic images.
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245 1 0 $a Digital processing of neurologic images.
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500 $a Source: Dissertation Abstracts International, Volume: 76-07(E), Section: B.
500 $a Adviser: Bradley J. Erickson.
502 $a Thesis (Ph.D.)--College of Medicine - Mayo Clinic, 2015.
506 $a This item is not available from ProQuest Dissertations & Theses.
520 $a Digital processing can be used to greatly enhance the utility of medical images. This document includes analysis and development of multiple digital image processing methods, both individually and in aggregate, for neurologic image applications. We investigated parameter optimization and novel extension of the nonlocal means denoising algorithm, showing that using a very small search window can result in increased denoising performance with proper adjustment of the other parameters, and that the nonlocal property can be exploited to use thick slice reconstructions in denoising thin slice reconstructions. After developing a whole brain segmentation algorithm for a valuable set of magnetic resonance (MR) exams of multiple sclerosis patients with biopsy-proven immunopattern classifications, we present analysis showing no significant tissue- and acquisition-specific MR signal intensity differences between the immunopatterns. Finally, we discovered clinically significant differences in measurement output from FDA-approved software used for computing cerebral blood volume maps from dynamic susceptibility contrast MR images. The potential clinical impact of these differences is shown to be disagreement between the software 20-50% of the time regarding classification of post-radiation treatment glioblastoma multiforme patients as having progressing or pseudoprogressing tumor. Additionally, the results indicate that 3.0 T MR acquisitions provide more useful perfusion information for identification of tumor pseudoprogression than 1.5 T acquisitions.
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