We perform a parametric study of the newly developed time-of-flight (TOF) image reconstruction algorithm, proposed for real-time imaging in total-body Jagiellonian PET (J-PET) scanners. The asymmetric 3D filtering kernel is applied at each most likely position electron-positron annihilation, estimated from emissions back-to-back γ-photons. optimisation its parameters studied using Monte Carlo s...

We develop a new filter which combines spatially adaptive noise filtering in the wavelet domain and temporal filtering in the signal domain. For spatial filtering, we propose a new wavelet shrinkage method, which estimates how probable it is that a wavelet coefficient represents a “signal of interest” given its value, given the locally averaged coefficient magnitude and given the global subband...

A number of different methods have been demonstrated which increase the speed of MR acquisition by decreasing the number of sequential phase encodes. The UNFOLD technique is based on time interleaving of k-space lines in sequential images and exploits the property that the outer portion of the field-of-view is relatively static. The differences in spatial sensitivity of multiple receiver coils ...

In the visual system, diverse image processing starts with bipolar cells, which are the second-order neurons of the retina. Thirteen subtypes of bipolar cells have been identified, which are thought to encode different features of image signaling and to initiate distinct signal-processing streams. Although morphologically identified, the functional roles of each bipolar cell subtype in visual s...

Filtering noise in image sequences is an important preprocessing task in many image processing applications, including but not limited to real-time x-ray image sequences obtained in angiography. The main objective in real-time noise filtering is to improve the quality of the resultant image sequences. Practically affordable approaches are generally suboptimal and deal with the spatial and tempo...

We propose a robust and effective mesh denoising approach consisting of three steps: vertex pre-filtering, L1-median normal filtering, and vertex updating. Given an input noisy mesh model, our method generates a high quality model that preserves geometric features. Our approach is more robust than state of the art approaches when denoising models with different levels of noise and can handle mo...