Abstract
Multimodality imaging is becoming increasingly important in medical imaging. Since the motivation for combining multiple imaging modalities is generally to improve diagnostic or prognostic accuracy, the benefits of multimodality imaging cannot be assessed through the display of example images. Instead, we must use objective, task-based measures of image quality to draw valid conclusions about system performance. In this paper, we will present a general framework for utilizing objective, task-based measures of image quality in assessing multimodality and adaptive imaging systems. We introduce a classification scheme for multimodality and adaptive imaging systems and provide a mathematical description of the imaging chain along with block diagrams to provide a visual illustration. We show that the task-based methodology developed for evaluating single-modality imaging can be applied, with minor modifications, to multimodality and adaptive imaging. We discuss strategies for practical implementing of task-based methods to assess and optimize multimodality imaging systems.
| Original language | English (US) |
|---|---|
| Article number | 4446232 |
| Pages (from-to) | 500-511 |
| Number of pages | 12 |
| Journal | Proceedings of the IEEE |
| Volume | 96 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 2008 |
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Keywords
- Adaptive imaging
- Image quality
- Multimodality
ASJC Scopus subject areas
- Electrical and Electronic Engineering
Cite this
A task-based approach to adaptive and multimodality imaging. / Clarkson, Eric W; Kupinski, Matthew A; Barrett, Harrison H; Furenlid, Lars R.
In: Proceedings of the IEEE, Vol. 96, No. 3, 4446232, 03.2008, p. 500-511.Research output: Contribution to journal › Article
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TY - JOUR
T1 - A task-based approach to adaptive and multimodality imaging
AU - Clarkson, Eric W
AU - Kupinski, Matthew A
AU - Barrett, Harrison H
AU - Furenlid, Lars R
PY - 2008/3
Y1 - 2008/3
N2 - Multimodality imaging is becoming increasingly important in medical imaging. Since the motivation for combining multiple imaging modalities is generally to improve diagnostic or prognostic accuracy, the benefits of multimodality imaging cannot be assessed through the display of example images. Instead, we must use objective, task-based measures of image quality to draw valid conclusions about system performance. In this paper, we will present a general framework for utilizing objective, task-based measures of image quality in assessing multimodality and adaptive imaging systems. We introduce a classification scheme for multimodality and adaptive imaging systems and provide a mathematical description of the imaging chain along with block diagrams to provide a visual illustration. We show that the task-based methodology developed for evaluating single-modality imaging can be applied, with minor modifications, to multimodality and adaptive imaging. We discuss strategies for practical implementing of task-based methods to assess and optimize multimodality imaging systems.
AB - Multimodality imaging is becoming increasingly important in medical imaging. Since the motivation for combining multiple imaging modalities is generally to improve diagnostic or prognostic accuracy, the benefits of multimodality imaging cannot be assessed through the display of example images. Instead, we must use objective, task-based measures of image quality to draw valid conclusions about system performance. In this paper, we will present a general framework for utilizing objective, task-based measures of image quality in assessing multimodality and adaptive imaging systems. We introduce a classification scheme for multimodality and adaptive imaging systems and provide a mathematical description of the imaging chain along with block diagrams to provide a visual illustration. We show that the task-based methodology developed for evaluating single-modality imaging can be applied, with minor modifications, to multimodality and adaptive imaging. We discuss strategies for practical implementing of task-based methods to assess and optimize multimodality imaging systems.
KW - Adaptive imaging
KW - Image quality
KW - Multimodality
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U2 - 10.1109/JPROC.2007.913553
DO - 10.1109/JPROC.2007.913553
M3 - Article
AN - SCOPUS:51049120514
VL - 96
SP - 500
EP - 511
JO - Proceedings of the IEEE
JF - Proceedings of the IEEE
SN - 0018-9219
IS - 3
M1 - 4446232
ER -