Abstract
Recently, detective quantum efficiency (DQE) arising from the concept of signal-to-noise ratio (SNR) has been used for assessing digital x-ray imaging systems. Using a phase-shift of x-rays that occurs when passing through an object, digital phase contrast imaging (herein referred to as "phase imaging"), which involves magnification, can produce images different from those of standard contact imaging (herein referred to as "regular imaging"). For this reason, assessment of the image quality based on DQE which does not include the object information may not be appropriate to compare image quality between the phase images and the regular images. As an alternative method, we proposed a new image quality assessment method based on radial direction distribution function (RDDF) and signal intensity distribution function (SIDF) in two-dimensional power spectra of images that contain information of an object. To evaluate the usefulness of our method based on RDDF and SIDF, we assessed images of different contrast, noise characteristic and sharpness using simple phantoms. Our results showed that the accurate evaluation of these factors was successfully performed. Comparing the image quality of projected plant seeds by phase imaging and regular imaging, we found the phase imaging method provided higher image quality in terms of edge sharpness than that of the regular imaging.
| Original language | English |
|---|---|
| Title of host publication | Digital Mammography - 10th International Workshop, IWDM 2010, Proceedings |
| Pages | 137-144 |
| Number of pages | 8 |
| DOIs | |
| Publication status | Published - Jul 21 2010 |
| Event | 10th International Workshop on Digital Mammography, IWDM 2010 - Girona, Catalonia, Spain Duration: Jun 16 2010 → Jun 18 2010 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 6136 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 10th International Workshop on Digital Mammography, IWDM 2010 |
|---|---|
| Country | Spain |
| City | Girona, Catalonia |
| Period | 6/16/10 → 6/18/10 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
Cite this
Introducing a novel image quality measure for digital phase-contrast-image evaluation. / Matsuo, Satoru; Fujita, Hiroshi; Morishita, Junji; Katafuchi, Tetsuro.
Digital Mammography - 10th International Workshop, IWDM 2010, Proceedings. 2010. p. 137-144 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6136 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Introducing a novel image quality measure for digital phase-contrast-image evaluation
AU - Matsuo, Satoru
AU - Fujita, Hiroshi
AU - Morishita, Junji
AU - Katafuchi, Tetsuro
PY - 2010/7/21
Y1 - 2010/7/21
N2 - Recently, detective quantum efficiency (DQE) arising from the concept of signal-to-noise ratio (SNR) has been used for assessing digital x-ray imaging systems. Using a phase-shift of x-rays that occurs when passing through an object, digital phase contrast imaging (herein referred to as "phase imaging"), which involves magnification, can produce images different from those of standard contact imaging (herein referred to as "regular imaging"). For this reason, assessment of the image quality based on DQE which does not include the object information may not be appropriate to compare image quality between the phase images and the regular images. As an alternative method, we proposed a new image quality assessment method based on radial direction distribution function (RDDF) and signal intensity distribution function (SIDF) in two-dimensional power spectra of images that contain information of an object. To evaluate the usefulness of our method based on RDDF and SIDF, we assessed images of different contrast, noise characteristic and sharpness using simple phantoms. Our results showed that the accurate evaluation of these factors was successfully performed. Comparing the image quality of projected plant seeds by phase imaging and regular imaging, we found the phase imaging method provided higher image quality in terms of edge sharpness than that of the regular imaging.
AB - Recently, detective quantum efficiency (DQE) arising from the concept of signal-to-noise ratio (SNR) has been used for assessing digital x-ray imaging systems. Using a phase-shift of x-rays that occurs when passing through an object, digital phase contrast imaging (herein referred to as "phase imaging"), which involves magnification, can produce images different from those of standard contact imaging (herein referred to as "regular imaging"). For this reason, assessment of the image quality based on DQE which does not include the object information may not be appropriate to compare image quality between the phase images and the regular images. As an alternative method, we proposed a new image quality assessment method based on radial direction distribution function (RDDF) and signal intensity distribution function (SIDF) in two-dimensional power spectra of images that contain information of an object. To evaluate the usefulness of our method based on RDDF and SIDF, we assessed images of different contrast, noise characteristic and sharpness using simple phantoms. Our results showed that the accurate evaluation of these factors was successfully performed. Comparing the image quality of projected plant seeds by phase imaging and regular imaging, we found the phase imaging method provided higher image quality in terms of edge sharpness than that of the regular imaging.
UR - http://www.scopus.com/inward/record.url?scp=77954632745&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77954632745&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-13666-5_19
DO - 10.1007/978-3-642-13666-5_19
M3 - Conference contribution
AN - SCOPUS:77954632745
SN - 3642136656
SN - 9783642136658
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 137
EP - 144
BT - Digital Mammography - 10th International Workshop, IWDM 2010, Proceedings
ER -