Evaluation of Origin Ensemble algorithm for image reconstruction for pixelated solid-state detectors with large number of channels

Kolstein, M.; Lorenzo, G. De; Mikhaylova, Ekaterina; Chmeissani, M.; Ariño, G; Calderon, Yonatan; Ozsahin, Ilker; Uzun, D.

doi:10.1088/1748-0221/8/04/p04030

Cited by 6 publications

(4 citation statements)

References 16 publications

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“…We adopted SOE as an iterative algorithm without ML-EM (and advanced method of ML-EM), as well as the analytical method developed by Tomitani and Hirasawa. These methods have been used in previous comparison studies [28][29][30][31]. Nuclear medical images require the ability to PLOS ONE identify disease.…”

Section: Discussionmentioning

confidence: 99%

Improved iterative reconstruction method for Compton imaging using median filter

et al. 2020

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A Compton camera is a device for imaging a radio-source distribution without using a mechanical collimator. Ordered-subset expectation-maximization (OS-EM) is widely used to reconstruct Compton images. However, the OS-EM algorithm tends to over-concentrate and amplify noise in the reconstructed image. It is, thus, necessary to optimize the number of iterations to develop high-quality images, but this has not yet been achieved. In this paper, we apply a median filter to an OS-EM algorithm and introduce a median root prior expectation-maximization (MRP-EM) algorithm to overcome this problem. In MRP-EM, the median filter is used to update the image in each iteration. We evaluated the quality of images reconstructed by our proposed method and compared them with those reconstructed by conventional algorithms using mathematical phantoms. The spatial resolution was estimated using the images of two point sources. Reproducibility was evaluated on an ellipsoidal phantom by calculating the residual sum of squares, zero-mean normalized cross-correlation, and mutual information. In addition, we evaluated the semi-quantitative performance and uniformity on the ellipsoidal phantom. MRP-EM reduces the generated noise and is robust with respect to the number of iterations. An evaluation of the reconstructed image quality using some statistical indices shows that our proposed method delivers better results than conventional techniques.

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Section: Discussionmentioning

confidence: 99%

Improved iterative reconstruction method for Compton imaging using median filter

et al. 2020

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“…Future work will include the improvement of the spatial resolution in all directions by further studies on rotating the Compton camera, the study on how to approximate the transition probability t ik and the sensitivity s j of the LM-OSEM algorithm and a systematic comparison of the performance of LM-OSEM and other algorithms for Compton camera (e.g. OE, as reported in [17]) with various phantoms. Additionally, it has to be studied how to diminish the artefacts in the edges and, especially, the corners of the images.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of list-mode ordered subset expectation maximization image reconstruction for pixelated solid-state compton gamma camera with large number of channels

2014

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The Voxel Imaging PET (VIP) Pathfinder project intends to show the advantages of using pixelated solid-state technology for nuclear medicine applications. It proposes designs for Positron Emission Tomography (PET), Positron Emission Mammography (PEM) and Compton gamma camera detectors with a large number of signal channels (of the order of 106). For Compton camera, especially with a large number of readout channels, image reconstruction presents a big challenge. In this work, results are presented for the List-Mode Ordered Subset Expectation Maximization (LM-OSEM) image reconstruction algorithm on simulated data with the VIP Compton camera design. For the simulation, all realistic contributions to the spatial resolution are taken into account, including the Doppler broadening effect. The results show that even with a straightforward implementation of LM-OSEM, good images can be obtained for the proposed Compton camera design. Results are shown for various phantoms, including extended sources and with a distance between the field of view and the first detector plane equal to 100 mm which corresponds to a realistic nuclear medicine environment.

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“…In our laboratory we have implemented it for 3-D PET data from a time-of-flight (TOF) list-mode lanthanum-bromide system [24] and for the Siemens Biograph 3-D PET [25]. We and other investigators have used it for analysis of data from a Compton camera and solid state detectors [26]–[28]. Other investigators have also used it in applications for radiotherapy [29].…”

Section: Discussionmentioning

confidence: 99%

Evaluation of Imaging Systems Using the Posterior Variance of Emission Counts

Sitek

Moore

2013

IEEE Trans. Med. Imaging

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We investigate an approach to evaluation of emission-tomography (ET) imaging systems used for region-of-interest (ROI) estimation tasks. In the evaluation we employ the concept of "emission counts" (EC), which are the number of events per voxel emitted during a scan. We use the reduction in posterior variance of ROI EC, compared to the prior ROI EC variance, as the metric of primary interest, which we call the "posterior variance reduction index" (PVRI). Systems that achieve a higher PVRI are considered superior to systems with lower PVRI. The approach is independent of the reconstruction method and is applicable to all photon-limited data types including list-mode data. We analyzed this approach using a model of 2-D tomography, and compared our results to the classical theory of tomographic sampling. We found that performance evaluations using the PVRI index were consistent with the classical theory. System evaluation based on EC posterior variance is an intuitively appealing and physically meaningful method that is useful for evaluation of system performance in ROI quantitation tasks.

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Evaluation of Origin Ensemble algorithm for image reconstruction for pixelated solid-state detectors with large number of channels

Cited by 6 publications

References 16 publications

Improved iterative reconstruction method for Compton imaging using median filter

Improved iterative reconstruction method for Compton imaging using median filter

Evaluation of list-mode ordered subset expectation maximization image reconstruction for pixelated solid-state compton gamma camera with large number of channels

Evaluation of Imaging Systems Using the Posterior Variance of Emission Counts

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