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Image Search Results
Journal: PLOS Computational Biology
Article Title: Coupling and heterogeneity modulate pacemaking capability in healthy and diseased two-dimensional sinoatrial node tissue models
doi: 10.1371/journal.pcbi.1010098
Figure Lengend Snippet: Hardware and software specification for model reproducibility.
Article Snippet: Simulation , MATLAB R2019b;
Techniques: Software
Journal: Scientific Reports
Article Title: Model based noise correction enhances the accuracy of pancreatic CT perfusion blood flow measurements
doi: 10.1038/s41598-025-24482-x
Figure Lengend Snippet: A detailed explanation of the output obtained at each step during development of the noise correction algorithm. ( a ) An arterial input function (AIF) of a digital perfusion phantom (DPP) with zero baseline and temporal sampling rate of 1.5 s, generated by averaging the AIFs from a cohort of 59 pancreatic ductal adenocarcinoma (PDAC) patients. ( b ) An example of the simulated impulse response function (IRF) of a DPP. ( c ) An example of noise-free and noise-added tissue attenuation curves (TACs) for a DPP generated for both tissue types, PDAC and non-neoplastic pancreatic parenchyma. ( d ) An example of TACs from non-neoplastic pancreatic parenchyma and PDAC regions of a PDAC patient for comparison with the simulated TACs. ( e ) An example of an image from the DICOM series of a DPP made up of 16,128 (28 sets of ground-truth values * 576 random noise samples) TACs. The top right corner of the phantom image represents the AIF. ( f ) An example of a blood flow (BF) map obtained from a DPP using commercially available CT perfusion software (syngo.via Body perfusion VB10B, Siemens Healthineers).
Article Snippet: The algorithm was implemented in MATLAB R2022a (MathWorks; USA) and evaluated using a commercially available workstation (
Techniques: Sampling, Generated, Comparison, Software