
doi: 10.3233/bme-151396
pmid: 26405855
Abstract Segmentation technique is widely accepted to reduce noise propagation from transmission scanning for positron emission tomography. The conventional routine is to sequentially perform reconstruction and segmentation. A smoothness penalty is also usually used to reduce noise, which can be imposed to both the ML and WLS estimators. In this paper we replace the smoothness penalty by a segmentation penalty that biases the object toward piecewise-homogeneous reconstruction. Two updating algorithms are developed to solve the penalized ML and WLS estimates, which monotonically decrease the cost functions. Experimental results on simulated phantom and real clinical data were both given to demonstrate the effectiveness and efficiency of the algorithms which were proposed.
Phantoms, Imaging, Positron-Emission Tomography, Image Processing, Computer-Assisted, Humans, Poisson Distribution, Algorithms
Phantoms, Imaging, Positron-Emission Tomography, Image Processing, Computer-Assisted, Humans, Poisson Distribution, Algorithms
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
