Theoretical Analysis of Penalized Maximum-Likelihood Patlak Parametric Image Reconstruction in Dynamic PET for Lesion Detection.

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Direct Patlak Reconstruction From Dynamic PET Data Using the Kernel Method With MRI Information Based on Structural Similarity.Relative Patlak plot for dynamic PET parametric imaging without the need for early-time input function

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Theoretical Analysis of Penalized Maximum-Likelihood Patlak Parametric Image Reconstruction in Dynamic PET for Lesion Detection.

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http://www.wikidata.org/entity/Q37201183

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2015 nî lūn-bûn

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2015年の論文

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2015年学术文章

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2015年学术文章

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2015年学术文章

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2015年学术文章

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2015年學術文章

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Theoretical Analysis of Penali ...... amic PET for Lesion Detection.

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Theoretical Analysis of Penali ...... amic PET for Lesion Detection.

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Theoretical Analysis of Penali ...... amic PET for Lesion Detection.

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Theoretical Analysis of Penali ...... amic PET for Lesion Detection.

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Theoretical Analysis of Penali ...... amic PET for Lesion Detection.

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Theoretical Analysis of Penali ...... amic PET for Lesion Detection.

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P1476

Theoretical Analysis of Penali ...... namic PET for Lesion Detection

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P2093

Li Yang

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P2860

Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data

A theoretical study of the contrast recovery and variance of MAP reconstructions from PET data.

Evaluation of the channelized Hotelling observer with an internal-noise model in a train-test paradigm for cardiac SPECT defect detection

Human- and model-observer performance in ramp-spectrum noise: effects of regularization and object variability.

Acceleration of the direct reconstruction of linear parametric images using nested algorithms

Regularization design in penalized maximum-likelihood image reconstruction for lesion detection in 3D PET.

Evaluation of penalty design in penalized maximum-likelihood image reconstruction for lesion detection.

Patlak image estimation from dual time-point list-mode PET data

Comparison of Lesion Detection and Quantification in MAP Reconstruction with Gaussian and Non-Gaussian Priors.

Observer signal-to-noise ratios for the ML-EM algorithm.

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947-956

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scholarly article

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10.1109/TMI.2015.2502982

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Jinyi Qi

Guobao Wang

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2015-11-23T00:00:00Z

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26625407

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4996625

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Theoretical Analysis of Penalized Maximum-Likelihood Patlak Parametric Image Reconstruction in Dynamic PET for Lesion Detection.

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P2860

P2860

Theoretical Analysis of Penalized Maximum-Likelihood Patlak Parametric Image Reconstruction in Dynamic PET for Lesion Detection.

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