Fast LROC analysis of Bayesian reconstructed emission tomographic images using model observers.

@article{Khurd2005FastLA,
  title={Fast LROC analysis of Bayesian reconstructed emission tomographic images using model observers.},
  author={Parmeshwar Khurd and Gene Gindi},
  journal={Physics in medicine and biology},
  year={2005},
  volume={50 7},
  pages={
          1519-32
        }
}
Lesion detection and localization is an important task in emission computed tomography. Detection and localization performance with signal location uncertainty may be summarized by a scalar figure of merit, the area under the localization receiver operating characteristic (LROC) curve, A(LROC). We consider model observers to compute A(LROC) for two-dimensional maximum a posteriori (MAP) reconstructions. Model observers may be used to rapidly prototype studies that use human observers. We… CONTINUE READING
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