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Assessment of low contrast detection in CT using model observers: Developing a clinically-relevant tool for characterising adaptive statistical and model-based iterative reconstruction
- Source :
- Zeitschrift für Medizinische Physik. 27:86-97
- Publication Year :
- 2017
- Publisher :
- Elsevier BV, 2017.
-
Abstract
- Purpose This study aims to assess CT image quality in a way that would meet specific requirements of clinical practice. Physics metrics like Fourier transform derived metrics were traditionally employed for that. However, assessment methods through a detection task have also developed quite extensively lately, and we chose here to rely on this modality for image quality assessment. Our goal was to develop a tool adapted for a fast and reliable CT image quality assessment in order to pave the way for new CT benchmarking techniques in a clinical context. Additionally, we also used this method to estimate the benefits brought by some IR algorithms. Materials and methods A modified QRM chest phantom containing spheres of 5 and 8 mm at contrast levels of 10 and 20 HU at 120 kVp was used. Images of the phantom were acquired at CTDI vol of 0.8, 3.6, 8.2 and 14.5 mGy, before being reconstructed using FBP, ASIR 40 and MBIR on a GE HD 750 CT scanner. They were then assessed by eight human observers undergoing a 4-AFC test. After that, these data were compared with the results obtained from two different model observers (NPWE and CHO with DDoG channels). The study investigated the effects of the acquisition conditions as well as reconstruction methods. Results NPWE and CHO models both gave coherent results and approximated human observer results well. Moreover, the reconstruction technique used to retrieve the images had a clear impact on the PC values. Both models suggest that switching from FBP to ASIR 40 and particularly to MBIR produces an increase of the low contrast detection, provided a minimum level of exposure is reached. Conclusion Our work shows that both CHO with DDoG channels and NPWE models both approximate the trend of humans performing a detection task. Both models also suggest that the use of MBIR goes along with an increase of the PCs, indicating that further dose reduction is still possible when using those techniques. Eventually, the CHO model associated to the protocol we described in this study happened to be an efficient way to assess CT images in a clinical environment. In the future, this simple method could represent a sound basis to benchmark clinical practice and CT devices.
- Subjects :
- Iterative method
Image quality
Biophysics
Image processing
Context (language use)
Iterative reconstruction
Radiation Dosage
computer.software_genre
Imaging phantom
030218 nuclear medicine & medical imaging
03 medical and health sciences
0302 clinical medicine
Humans
Radiology, Nuclear Medicine and imaging
Mathematics
Observer Variation
Protocol (science)
Radiological and Ultrasound Technology
Phantoms, Imaging
business.industry
Pattern recognition
Benchmarking
030220 oncology & carcinogenesis
Radiographic Image Interpretation, Computer-Assisted
Artificial intelligence
Data mining
Tomography
Tomography, X-Ray Computed
business
computer
Algorithms
Subjects
Details
- ISSN :
- 09393889
- Volume :
- 27
- Database :
- OpenAIRE
- Journal :
- Zeitschrift für Medizinische Physik
- Accession number :
- edsair.doi.dedup.....dfa7645fe96a9fa86c0a9ef7dec5e104
- Full Text :
- https://doi.org/10.1016/j.zemedi.2016.04.002