55. A statistical method for assessing Low Contrast Detectability in CT: A phantom study using Filtered Back Projection and Iterative reconstructions. (December 2018)
- Record Type:
- Journal Article
- Title:
- 55. A statistical method for assessing Low Contrast Detectability in CT: A phantom study using Filtered Back Projection and Iterative reconstructions. (December 2018)
- Main Title:
- 55. A statistical method for assessing Low Contrast Detectability in CT: A phantom study using Filtered Back Projection and Iterative reconstructions
- Authors:
- Berta, L.
Colombo, P.E.
De Mattia, C.
Calderoni, F.
Nici, S.
Rottoli, F.
Artuso, E.
Moretti, R.
Torresin, A. - Abstract:
- Abstract : Purpose: To calculate Low Contrast Detectability (LCD) curves using a statistical approach on CT images reconstructed with filtered back projection (FBP) and Iterative (IR) algorithms. Methods: 25 axial images of a water phantom (25 cm diameter), scanned on a Somatom Definition Flash with different tube loads, were reconstructed with FBP and IR (IRIS) filters. A volume of 16 × 16 × 5 cm 3 (VOI-BIG) was divided in many smaller contiguous squared ROI (ROI-lets) drawn in each axial slice and the standard deviations (SDX-m) of their mean CT values (X-m) were calculated for different dimensions. Threshold (Th) for the detectability of a low contrast object can be predicted, for an ideal observer, as Th = 3.29 ∗ SDX-m, assuming a normal distribution of X-m with a confidence level of 95% and Signal-Known-Exactly/Background Known Exactly conditions. LCD curves were obtained with this method by increasing the dimensions of the ROI-lets from 2 mm (4 pixel) to 25 mm (52 pixel) for smooth, medium-smooth and sharp FBP filters together with their corresponding iterative versions at different dose levels (CTDIvol range: 2.8–20.7 mGy). Contrast Gain (CG) was defined as the difference between 2 LCD thresholds for the same object size. Results: Compared to FBP images, the noise in IR with CTDIvol = 6.9 mGy, calculated as pixel SD in the VOI-BIG, was reduced by 24%, 33% and 36% for smooth, medium-smooth and sharp filter respectively. This improvement in image quality resulted alsoAbstract : Purpose: To calculate Low Contrast Detectability (LCD) curves using a statistical approach on CT images reconstructed with filtered back projection (FBP) and Iterative (IR) algorithms. Methods: 25 axial images of a water phantom (25 cm diameter), scanned on a Somatom Definition Flash with different tube loads, were reconstructed with FBP and IR (IRIS) filters. A volume of 16 × 16 × 5 cm 3 (VOI-BIG) was divided in many smaller contiguous squared ROI (ROI-lets) drawn in each axial slice and the standard deviations (SDX-m) of their mean CT values (X-m) were calculated for different dimensions. Threshold (Th) for the detectability of a low contrast object can be predicted, for an ideal observer, as Th = 3.29 ∗ SDX-m, assuming a normal distribution of X-m with a confidence level of 95% and Signal-Known-Exactly/Background Known Exactly conditions. LCD curves were obtained with this method by increasing the dimensions of the ROI-lets from 2 mm (4 pixel) to 25 mm (52 pixel) for smooth, medium-smooth and sharp FBP filters together with their corresponding iterative versions at different dose levels (CTDIvol range: 2.8–20.7 mGy). Contrast Gain (CG) was defined as the difference between 2 LCD thresholds for the same object size. Results: Compared to FBP images, the noise in IR with CTDIvol = 6.9 mGy, calculated as pixel SD in the VOI-BIG, was reduced by 24%, 33% and 36% for smooth, medium-smooth and sharp filter respectively. This improvement in image quality resulted also in the LCD curves: an average CG of 0.4 HU and 2.3 HU was observed for smooth/medium and sharp filters for details dimension within 5 and 20 mm. When FBP-Smooth and IR-Medium/Smooth filters are compared, CG increase monotonically with dose reduction and object size. Conclusions: Although the proposed method is valid for ideal observers only, it provides a simple but potentially attractive metric for image quality assessment and protocol optimization. … (more)
- Is Part Of:
- Physica medica. Volume 56(2018)Supplement 2
- Journal:
- Physica medica
- Issue:
- Volume 56(2018)Supplement 2
- Issue Display:
- Volume 56, Issue 2 (2018)
- Year:
- 2018
- Volume:
- 56
- Issue:
- 2
- Issue Sort Value:
- 2018-0056-0002-0000
- Page Start:
- 97
- Page End:
- 98
- Publication Date:
- 2018-12
- Subjects:
- Medical physics -- Periodicals
Biophysics -- Periodicals
Biophysics -- Periodicals
Imagerie médicale -- Périodiques
Radiothérapie -- Périodiques
Rayons X -- Sécurité -- Mesures -- Périodiques
Physique -- Périodiques
Médecine -- Périodiques
610.153 - Journal URLs:
- http://www.sciencedirect.com/science/journal/11201797 ↗
http://www.clinicalkey.com/dura/browse/journalIssue/11201797 ↗
http://www.clinicalkey.com.au/dura/browse/journalIssue/11201797 ↗
http://www.elsevier.com/journals ↗
http://www.physicamedica.com ↗ - DOI:
- 10.1016/j.ejmp.2018.04.065 ↗
- Languages:
- English
- ISSNs:
- 1120-1797
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6475.070000
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