Maximum Likelihood Reconstruction for Emission Tomography

Abstract-We previously proposed a fast maximum a posteriori (MAP) algorithm, LBFGS-B-PC, combining LBFSG-B with diagonal preconditioning. Previous results have shown in simulations that it converges using around 40 projections independent of many factors. The aim of this study is to improve the algorithm further by using a better initial image and a modified preconditioner that is less sensitive to noise and data scale. By initializing the algorithm with the best initial image (one full iteration of OSEM with 35 subsets), ROI values can converge almost twice as fast for the same computation time. Moreover, the new preconditioner makes the performance more consistent between high and low count data sets. In addition, we have found a means to choose the stopping criteria to reach a desired quantitative accuracy level in the reconstructed image. Based on the results with patient data, the optimized LBFGS-B-PC shows promise for clinical imaging.

show abstract

“…In our previous study we used 1 iteration of MLEM [2] for initialisation. Here we will investigate the use of OSEM [3].…”

Section: E Algorithm Optimizationmentioning

confidence: 99%

Performance improvement and validation of a new MAP reconstruction algorithm

Tsai

Bousse

Stearns³

et al. 2016

2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop (NSS/MIC/R

View full text Add to dashboard Cite

show abstract

“…The relationship between the MLE and DPL is described in detail by Llacer 24 . The target function used in the algorithm is adapted from a PET image reconstruction algorithm developed by Shepp and Vardi 25 , 26 . The algorithm is robust in that it will always produce reasonable results.…”

Section: Methodsmentioning

confidence: 99%

Patient specific quality assurance for the delivery of intensity modulated radiotherapy

Agazaryan

Solberg

DeMarco

2003

J Applied Clin Med Phys

View full text Add to dashboard Cite

A patient specific quality assurance program has been developed to facilitate the clinical implementation of intensity modulated radiotherapy (IMRT) delivered using a micro‐multileaf collimator. The methodology includes several dosimetric tasks that are performed prior to the treatment of each patient. Film dosimetry is performed for each individual field and for the multifield composite plan. Individual field measurements are performed at a depth of 5 cm in a water equivalent slab phantom; export of dose calculations from the treatment planning system is similarly specified. For the composite distribution, parameters from the patient plan are applied to an IMRT phantom, and film is exposed in an axial orientation. Distributions are compared with the aid of software developed for the specific tasks. The measured and calculated dose distributions can be superimposed and positioned graphically using move, rotate, and mirror tools, as well as by specifying isocenter coordinates and using fiducial marks. Horizontal and vertical profiles are available for analysis. Dose difference, distance‐to‐agreement, and γ index, the minimum scaled multidimensional distance between a measurement and a calculation point determined in combined dose and physical distance space, are calculated along a specified isodose line and displayed. γ provides an excellent measure of disagreement between measurement and calculation for complex intensity distributions. We specify 3% dose difference and 3 mm distance as our scaling acceptability criteria. Absolute dosimetry for each composite plan is performed using an ionization chamber. To date, excellent agreement between measurements and calculations has been observed. © 2003 American College of Medical Physics.PACS number(s): 87.53.–j, 87.66.–a

show abstract

“…Different types of tomographic reconstruction algorithms, including filtered back projection (FBP) (Deans, 1983) and iterative algebraic reconstruction technique (i-ART) (Shepp & Vardi, 1982), are available. The reconstructor provides options for using both FBP and i-ART algorithms for tomographic reconstruction.…”

Section: Analytical and Iterative Tomographic Reconstructormentioning

confidence: 99%

TXM-Wizard: a program for advanced data collection and evaluation in full-field transmission X-ray microscopy

et al. 2012

View full text Add to dashboard Cite

Transmission X-ray microscopy (TXM) has been well recognized as a powerful tool for non-destructive investigation of the three-dimensional inner structure of a sample with spatial resolution down to a few tens of nanometers, especially when combined with synchrotron radiation sources. Recent developments of this technique have presented a need for new tools for both system control and data analysis. Here a software package developed in MATLAB for script command generation and analysis of TXM data is presented. The first toolkit, the script generator, allows automating complex experimental tasks which involve up to several thousand motor movements. The second package was designed to accomplish computationally intense tasks such as data processing of mosaic and mosaic tomography datasets; dual-energy contrast imaging, where data are recorded above and below a specific X-ray absorption edge; and TXM X-ray absorption near-edge structure imaging datasets. Furthermore, analytical and iterative tomography reconstruction algorithms were implemented. The compiled software package is freely available.

show abstract

Maximum Likelihood Reconstruction for Emission Tomography

Cited by 3,907 publications

References 8 publications

Performance improvement and validation of a new MAP reconstruction algorithm

Performance improvement and validation of a new MAP reconstruction algorithm

Patient specific quality assurance for the delivery of intensity modulated radiotherapy

TXM-Wizard: a program for advanced data collection and evaluation in full-field transmission X-ray microscopy

Contact Info

Product

Resources

About