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Statistical event reconstruction techniques can give better results for gamma cameras than the traditional centroid method. However, implementation of such techniques requires detailed knowledge of the photomultiplier tube light-response functions. Here we describe an iterative method which allows one to obtain the response functions from flood irradiation data without imposing strict requirements on the spatial uniformity of the event distribution. A successful application of the method for medical gamma cameras is demonstrated using both simulated and experimental data. An implementation of the iterative reconstruction technique capable of operating in real time is presented. We show that this technique can also be used for monitoring photomultiplier gain variations.

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ANTS2 is a simulation and data processing package developed for position sensitive detectors with Anger camera type readout. The simulation module of ANTS2 is based on ROOT package from CERN, which is used to store the detector geometry and to perform 3D navigation. The module is capable of simulating particle sources, performing particle tracking, generating photons of primary and secondary scintillation, tracing optical photons and generating photosensor signals. The reconstruction module features several position reconstruction methods based on the statistical reconstruction algorithms (including GPU-based implementations), artificial neural networks and k-NN searches. The module can process simulated as well as imported experimental data containing photosensor signals. A custom library for B-spline parameterization of spatial response of photosensors is implemented which can be used to calculate and parameterize the spatial response of a detector. The package includes a graphical user interface with an extensive set of configuration, visualization and analysis tools. ANTS2 is being developed with the focus on the iterative (adaptive) reconstruction of the detector response using flood field irradiation data. The package is implemented in C++ programming language and it is a multiplatform, open source project.

It remains an open question whether long-range disambiguation of ambiguous surface motion can be achieved in early visual cortex or instead in higher level regions, which concerns object/surface segmentation/integration mechanisms. We used a bistable moving stimulus that can be perceived as a pattern comprehending both visual hemi-fields moving coherently downward or as two widely segregated nonoverlapping component objects (in each visual hemi-field) moving separately inward. This paradigm requires long-range integration across the vertical meridian leading to interhemispheric binding. Our fMRI study (n = 30) revealed a close relation between activity in hMT+ and perceptual switches involving interhemispheric segregation/integration of motion signals, crucially under nonlocal conditions where components do not overlap and belong to distinct hemispheres. Higher signal changes were found in hMT+ in response to spatially segregated component (incoherent) percepts than to pattern (coherent) percepts. This did not occur in early visual cortex, unlike apparent motion, which does not entail surface segmentation. We also identified a role for top-down mechanisms in state transitions. Deconvolution analysis of switch-related changes revealed prefrontal, insula, and cingulate areas, with the right superior parietal lobule (SPL) being particularly involved. We observed that directed influences could emerge either from left or right hMT+ during bistable motion integration/segregation. SPL also exhibited significant directed functional connectivity with hMT+, during perceptual state maintenance (Granger causality analysis). Our results suggest that long-range interhemispheric binding of ambiguous motion representations mainly reflect bottom-up processes from hMT+ during perceptual state maintenance. In contrast, state transitions maybe influenced by high-level regions such as the SPL. Hum Brain Mapp 38:4882-4897, 2017. © 2017 Wiley Periodicals, Inc.