Theoretical analysis of lesion detectability in penalized maximum-likelihood patlak parametric image reconstruction using dynamic PET

Li Yang, Guobao Wang, Jinyi Qi

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

1 Citation (Scopus)

Abstract

Detecting cancerous lesion is a major clinical application in emission tomography. In previous work, we have studied penalized maximum-likelihood (PML) image reconstruction for lesion detection in static PET. Here we extend our theoretical analysis of static PET reconstruction to dynamic PET. We study both the conventional indirect reconstruction and direct reconstruction for Patlak parametric image estimation. In indirect reconstruction, Patlak parametric images are generated by reconstructing a sequence of dynamic PET images first and then performing Patlak analysis on the time activity curves (TACs) pixel-by-pixel. In direct reconstruction, Patlak parametric images are estimated directly from raw sinogram data by incorporating the Patlak model into the image reconstruction procedure. PML reconstruction is used in both the indirect and direct reconstruction methods. We use a channelized Hotelling observer (CHO) to assess lesion detectability in the Patlak slope image. Simplified expressions for evaluating the lesion detectability have been derived and applied to the selection of the regularization parameter value to maximize the lesion detectability. The proposed method is validated using computer-based Monte Carlo simulation. Good agreements between theoretical predictions and Monte Carlo results are observed. The theoretical formula also shows the benefit of the direct method in dynamic PET reconstruction for lesion detection.

Original languageEnglish (US)
Title of host publicationProceedings - International Symposium on Biomedical Imaging
PublisherIEEE Computer Society
Pages1188-1191
Number of pages4
Volume2015-July
ISBN (Print)9781479923748
DOIs
StatePublished - Jul 21 2015
Event12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 - Brooklyn, United States
Duration: Apr 16 2015Apr 19 2015

Other

Other12th IEEE International Symposium on Biomedical Imaging, ISBI 2015
CountryUnited States
CityBrooklyn
Period4/16/154/19/15

Fingerprint

Computer-Assisted Image Processing
Image reconstruction
Maximum likelihood
Pixels
Tomography

Keywords

  • dynamic PET
  • lesion detection
  • Patlak model
  • PML reconstruction

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Cite this

Yang, L., Wang, G., & Qi, J. (2015). Theoretical analysis of lesion detectability in penalized maximum-likelihood patlak parametric image reconstruction using dynamic PET. In Proceedings - International Symposium on Biomedical Imaging (Vol. 2015-July, pp. 1188-1191). [7164085] IEEE Computer Society. https://doi.org/10.1109/ISBI.2015.7164085

Theoretical analysis of lesion detectability in penalized maximum-likelihood patlak parametric image reconstruction using dynamic PET. / Yang, Li; Wang, Guobao; Qi, Jinyi.

Proceedings - International Symposium on Biomedical Imaging. Vol. 2015-July IEEE Computer Society, 2015. p. 1188-1191 7164085.

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

Yang, L, Wang, G & Qi, J 2015, Theoretical analysis of lesion detectability in penalized maximum-likelihood patlak parametric image reconstruction using dynamic PET. in Proceedings - International Symposium on Biomedical Imaging. vol. 2015-July, 7164085, IEEE Computer Society, pp. 1188-1191, 12th IEEE International Symposium on Biomedical Imaging, ISBI 2015, Brooklyn, United States, 4/16/15. https://doi.org/10.1109/ISBI.2015.7164085
Yang L, Wang G, Qi J. Theoretical analysis of lesion detectability in penalized maximum-likelihood patlak parametric image reconstruction using dynamic PET. In Proceedings - International Symposium on Biomedical Imaging. Vol. 2015-July. IEEE Computer Society. 2015. p. 1188-1191. 7164085 https://doi.org/10.1109/ISBI.2015.7164085
Yang, Li ; Wang, Guobao ; Qi, Jinyi. / Theoretical analysis of lesion detectability in penalized maximum-likelihood patlak parametric image reconstruction using dynamic PET. Proceedings - International Symposium on Biomedical Imaging. Vol. 2015-July IEEE Computer Society, 2015. pp. 1188-1191
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