Multimedia Image Encryption Analysis Based on High-Dimensional Chaos Algorithm

With the development of network and multimedia technology, multimedia communication has attracted the attention of researchers. Image encryption has become an urgent need for secure multimedia communication. Compared with the traditional encryption system, encryption algorithms based on chaos are easier to implement, which makes them more suitable for large-scale data encryption. The calculation method of image encryption proposed in this paper is a combination of high-dimensional chaotic systems. This algorithm is mainly used for graph mapping and used the Lorenz system to expand and replace them one by one. Studies have shown that this calculation method causes mixed pixel values, good diffusion performance, and strong key performance with strong resistance. The pixel of the encrypted picture is distributed relatively random, and the characteristics of similar loudness are not relevant. It is proved through experiments that the above calculation methods have strong safety performance.

Determination of dominant loop in dual loop atrial tachycardia with direct graph mapping: an alternative for entrainment mapping?

Funding Acknowledgements Type of funding sources: None. Background Entrainment mapping (EM) is an important tool to determine the mechanism of complex reentrant atrial tachycardias (ATs), mostly to distinguish dominant from bystander reentrant loops. However, entrainment maneuvers are challenging, time consuming and risk to end the tachycardia. Purpose Recently, we developed a novel method Directed Graph Mapping (DGM), using concepts of network theory, allowing to automatically determine AT reentry loops from the local activation times (LAT) of any clinical mapping system. DGM showed good performance: it correctly finds ablation target (100 % success rate) on simple AT cases and could automatically determine reentry loops confirmed by the expert electrophysiologist with EM in complex AT cases. Out of 32 single loop cases, 62.5 % was identified correctly with automated DGM and out of 6 true double loop cases, 83.3 %. Lower performance for single reentry complex cases compared to EM was mainly because DGM could not distinguish the dominant loop from additional bystander loops found by DGM. Hence, the purpose of this work was to develop additional algorithms which in case of multiple found DGM loops could automatically find the dominant loop and compare it with the results of EM. Methods We performed multiple simulations of various types of double loop reentry on a patient specific model of the left atrium. Based on a clinical case, double loops were simulated around a scar at the anterior wall (localized reentry) and the mitral valve (MV). LAT maps were determined similar as in the clinic. By varying the size of the scar in multiple steps, we obtained a transition from a regime of a dominant loop around the scar (small scar), to a true double loop and further to a regime of a dominant loop around the MV (large scar). We developed a novel DGM algorithm to determine the dominant loop from the region of collision (ROC) found from the vector field of the wavefront graph. The developed method was also tested on 8 clinical cases of double loop ATs with EM measurements. Results Our algorithm found the location of the ROC and determined the correct dominant loop in 100% of the simulated data. We tested this on 8 clinical cases of AT, and accuracy of the method was 75 %. Conclusions Determining the ROC in case of multiple loops in AT could correctly determine the dominant versus bystander loop, leading to the correct ablation target, without the need for further EM.

Directed graph mapping is able to distinguish between the true and false rotors in a complex in-silico excitation pattern

Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): Supported in part by Dirección General de Polı́tica Cientı́fica de la Generalitat Valenciana PROMETEU 2020/043 Background In realistic in-silico studies (Figure1, top row) it was shown that phase mapping PM (Figure 1, A) can detect the correct rotor as well as phantom rotors as an artefact of interpolation or due to the far field (Figure 1, B). After interpretation of the LAT, the far field detections could not be distinguished from the true rotor driving the excitation pattern. This can contribute to failure in Atrial Fibrillation (AF) ablation procedures. Objective We tested if the recently developed tool Directed Graph mapping (DGM) is less prone to far-field effects and interpolation artefacts than PM on the same in-silico data. DGM represents the excitation pattern as a directed network, from which the rotational activity is detected as cycles in that network. Methods Starting from the electrograms (EGMs) of the 64 electrode basket catheter, we interpolated to 957 equidistant electrodes and calculated local activation times (LATs) of the interpolated EGMs (Figure 1, C). We varied the minimal allowed conduction velocity and calculated the corresponding networks for the complete simulation time. Detections were considered as correct if they were located in the same region of the true core of the phasemaps. The false detections were classified in multiple different regions (Figure 1, D). Results We find that by proper choice of CVs in the graphs it is possible to achieve a 80% detection of true rotors with 26% detection of false rotors. Reducing restrictions on the CVs increased the detection rate of the false rotors. False rotors due to artifacts were not detected by DGM (Figure 1, last row). Conclusion DGM is able to distinguish between true and far field rotors. False detections due to interpolation artifacts as seen in the PM protocol were not observed. The velocity limits in the graph construction play a keyrole in eliminating the far field effects. Abstract Figure 1