Abstract
Statistical reconstruction methods based on the penalized maximum-likelihood (or maximum a posteriori) principle have been developed to improve the image quality in emission tomography. However, the penalty functions (or image priors) are often heuristically designed to encourage smoothness in reconstructed images. This paper presents a method to design the penalty function to improve lesion detection. We factorize the penalty function into pairwise potentials. Using the theoretical expressions that we have developed for evaluating lesion detectability, we are able to find the optimum weights of the pairwise potentials to achieve the maximum lesion detectability based on the numerical observers that are correlated to human performance.
| Original language | English (US) |
|---|---|
| Title of host publication | 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano |
| Pages | 348-351 |
| Number of pages | 4 |
| Volume | 1 |
| State | Published - 2004 |
| Externally published | Yes |
| Event | 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano - Arlington, VA, United States Duration: Apr 15 2004 → Apr 18 2004 |
Other
| Other | 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano |
|---|---|
| Country | United States |
| City | Arlington, VA |
| Period | 4/15/04 → 4/18/04 |
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ASJC Scopus subject areas
- Engineering(all)
Cite this
Maximum-lesion-detectability reconstruction using penalized maximum likelihood. / Qi, Jinyi; Huesman, Ronald H.
2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano. Vol. 1 2004. p. 348-351.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Maximum-lesion-detectability reconstruction using penalized maximum likelihood
AU - Qi, Jinyi
AU - Huesman, Ronald H.
PY - 2004
Y1 - 2004
N2 - Statistical reconstruction methods based on the penalized maximum-likelihood (or maximum a posteriori) principle have been developed to improve the image quality in emission tomography. However, the penalty functions (or image priors) are often heuristically designed to encourage smoothness in reconstructed images. This paper presents a method to design the penalty function to improve lesion detection. We factorize the penalty function into pairwise potentials. Using the theoretical expressions that we have developed for evaluating lesion detectability, we are able to find the optimum weights of the pairwise potentials to achieve the maximum lesion detectability based on the numerical observers that are correlated to human performance.
AB - Statistical reconstruction methods based on the penalized maximum-likelihood (or maximum a posteriori) principle have been developed to improve the image quality in emission tomography. However, the penalty functions (or image priors) are often heuristically designed to encourage smoothness in reconstructed images. This paper presents a method to design the penalty function to improve lesion detection. We factorize the penalty function into pairwise potentials. Using the theoretical expressions that we have developed for evaluating lesion detectability, we are able to find the optimum weights of the pairwise potentials to achieve the maximum lesion detectability based on the numerical observers that are correlated to human performance.
UR - http://www.scopus.com/inward/record.url?scp=17144368446&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=17144368446&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:17144368446
SN - 0780383885
VL - 1
SP - 348
EP - 351
BT - 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano
ER -