Lesion insertion in projection domain for computed tomography image quality assessment

Baiyu Chen, Chi Ma, Zhicong Yu, Shuai Leng, Lifeng Yu, Cynthia H McCollough

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

To perform task-based image quality assessment in CT, it is desirable to have a large number of realistic patient images with known diagnostic truth. One effective way to achieve this objective is to create hybrid images that combine patient images with simulated lesions. Because conventional hybrid images generated in the image-domain fails to reflect the impact of scan and reconstruction parameters on lesion appearance, this study explored a projection-domain approach. Liver lesion models were forward projected according to the geometry of a commercial CT scanner to acquire lesion projections. The lesion projections were then inserted into patient projections (decoded from commercial CT raw data with the assistance of the vendor) and reconstructed to acquire hybrid images. To validate the accuracy of the forward projection geometry, simulated images reconstructed from the forward projections of a digital ACR phantom were compared to physically acquired ACR phantom images. To validate the hybrid images, lesion models were inserted into patient images and visually assessed. Results showed that the simulated phantom images and the physically acquired phantom images had great similarity in terms of HU accuracy and high-contrast resolution. The lesions in the hybrid image had a realistic appearance and merged naturally into the liver background. In addition, the inserted lesion demonstrated reconstruction-parameter-dependent appearance. Compared to conventional image-domain approach, our method enables more realistic hybrid images for image quality assessment.

Original languageEnglish (US)
Title of host publicationProgress in Biomedical Optics and Imaging - Proceedings of SPIE
PublisherSPIE
Volume9412
ISBN (Print)9781628415025
DOIs
StatePublished - 2015
EventMedical Imaging 2015: Physics of Medical Imaging - Orlando, United States
Duration: Feb 22 2015Feb 25 2015

Other

OtherMedical Imaging 2015: Physics of Medical Imaging
CountryUnited States
CityOrlando
Period2/22/152/25/15

Fingerprint

Liver
lesions
Image quality
Tomography
insertion
tomography
projection
Geometry
liver
geometry
scanners

Keywords

  • Computed tomography (CT)
  • Hybrid images
  • Image quality assessment
  • Lesion insertion

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

Cite this

Chen, B., Ma, C., Yu, Z., Leng, S., Yu, L., & McCollough, C. H. (2015). Lesion insertion in projection domain for computed tomography image quality assessment. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE (Vol. 9412). [94121R] SPIE. https://doi.org/10.1117/12.2082049

Lesion insertion in projection domain for computed tomography image quality assessment. / Chen, Baiyu; Ma, Chi; Yu, Zhicong; Leng, Shuai; Yu, Lifeng; McCollough, Cynthia H.

Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 9412 SPIE, 2015. 94121R.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chen, B, Ma, C, Yu, Z, Leng, S, Yu, L & McCollough, CH 2015, Lesion insertion in projection domain for computed tomography image quality assessment. in Progress in Biomedical Optics and Imaging - Proceedings of SPIE. vol. 9412, 94121R, SPIE, Medical Imaging 2015: Physics of Medical Imaging, Orlando, United States, 2/22/15. https://doi.org/10.1117/12.2082049
Chen B, Ma C, Yu Z, Leng S, Yu L, McCollough CH. Lesion insertion in projection domain for computed tomography image quality assessment. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 9412. SPIE. 2015. 94121R https://doi.org/10.1117/12.2082049
Chen, Baiyu ; Ma, Chi ; Yu, Zhicong ; Leng, Shuai ; Yu, Lifeng ; McCollough, Cynthia H. / Lesion insertion in projection domain for computed tomography image quality assessment. Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 9412 SPIE, 2015.
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