eprintid: 844
rev_number: 17
eprint_status: archive
userid: 35
dir: disk0/00/00/08/44
datestamp: 2011-09-08 12:36:10
lastmod: 2013-03-05 15:39:03
status_changed: 2011-09-08 12:36:10
type: conference_item
metadata_visibility: show
item_issues_count: 0
creators_name: Tsaftaris, Sotirios A.
creators_name: Zhou, Xiangzhi 
creators_name: Dharmakumar, Rohan
creators_id: sotirios.tsaftaris@imtlucca.it
creators_id: 
creators_id: 
title: Automated assessment of ghost artifacts in MRI
ispublished: unpub
subjects: QA76
subjects: RC
subjects: TK
divisions: CSA
full_text_status: none
pres_type: poster
abstract: Flow artifacts in MR images can appear as image ghosts within and outside the body cavity. Technical improvements aimed at suppressing these image ghosts often rely on expert scoring (1,2) or on semi-automated methods demanding tissue segmentation and estimation of statistical properties of intensity distribution (3) to evaluate the efficacy of the methods. These approaches can be labor intensive, introduce observer bias, computationally demanding, and error-prone if tissue segmentation is used. Herein we propose two fully automated image-processing methods that rely on the statistical properties of background (noise) pixels to assess the presence of flow artifacts (appearing as image ghosts) without requiring tissue segmentation. The first method rapidly evaluates the presence of flow artifacts in a global fashion, while the second one provides a more detailed characterization
of the artifacts. We evaluate the proposed methods in the setting of cardiac phase-resolved myocardial blood-oxygen-level-dependent (BOLD) MRI where different cine SSFP imaging strategies are proposed for overcoming flow artifacts. Finally we assess the utility of our automated approaches against expert scoring results.
date: 2010
event_title: 18th Meeting of the international society for magnetic resonance in medicine
event_location:  Stockholm, Sweden
event_dates: 1-7 May 2010
event_type: conference
refereed: TRUE
official_url: http://eta2.bio.cmu.edu/ISMRM/ISMRM%202010%20Stockholm/files/5087_2682.pdf
citation:   Tsaftaris, Sotirios A. and Zhou, Xiangzhi  and Dharmakumar, Rohan  Automated assessment of ghost artifacts in MRI.  In: 18th Meeting of the international society for magnetic resonance in medicine, 1-7 May 2010,  Stockholm, Sweden       (Unpublished)   (2010)