Scaling on a Dissipative Standard Mapping

2021 ◽  
pp. 163-169
Author(s):  
Edson Denis Leonel
Keyword(s):  
Standard Mapping

Asymptotic behavior of trajectories of a standard mapping

1986 ◽  
Vol 39 (5) ◽  
pp. 395-399
Author(s):  
L. D. Pustyl'nikov
Keyword(s):  
Asymptotic Behavior ◽  
Standard Mapping

scholarly journals Characterization of fibrillatory rhythms by ensemble vector directional analysis

2003 ◽  
Vol 285 (4) ◽  
pp. H1705-H1719 ◽  
Author(s):  
Alan Kadish ◽  
David Johnson ◽  
Willie Choe ◽  
Jeffrey Goldberger ◽  
George Horvath
Keyword(s):  
Atrial Fibrillation ◽  
Ventricular Fibrillation ◽  
Objective Assessment ◽  
Atrial Pacing ◽  
Activation Patterns ◽  
Standard Mapping ◽  
Vector Index ◽  
Mapping Techniques ◽  
Different Characteristics ◽  
Vector Mapping

Recent studies have demonstrated that fibrillatory rhythms are not random phenomena but have definable patterns. However, standard mapping techniques may have limitations in their ability to identify the organization of fibrillation. The purpose of this study was to develop and apply a method, “ensemble vector mapping,” for characterizing the spatiotemporal organization of fibrillation. Ventricular fibrillation was induced by burst pacing in normal mongrel dogs. In a separate protocol, atrial fibrillation was induced by epicardial aconitine application. Epicardial electrograms were recorded from a 112-electrode plaque array using a computerized mapping system. Vectors were created by summing orthogonal bipolar electrograms. The magnitude of the vectors was transformed using a logarithmic function, integrated over time, and normalized for local electrogram amplitude to produce an “ensemble vector” index whose magnitude is high when beat-to-beat activation direction is consistent and low when activation direction is variable. The mean index was 137 ± 36 mV/s during ventricular pacing at a cycle length of 300 ms but only 39 ± 23 mV/s during ventricular fibrillation ( P < 0.001). The ensemble vector index was also lower during atrial fibrillation (60 ± 54 mV/s) than during atrial pacing (115 ± 27 mV/s, P < 0.01 vs. atrial fibrillation) but not as low as during ventricular fibrillation ( P < 0.05, atrial vs. ventricular fibrillation). The index was also capable of distinguishing atrial tachycardia from atrial fibrillation. Ensemble vector mapping produces an objective assessment of the consistency of myocardial activation during fibrillation. The consistency of activation direction differs in different models of fibrillation and is higher during atrial than ventricular fibrillation. This technique has the potential to rapidly characterize repetitive activation patterns in fibrillatory rhythms and may help distinguish among different characteristics of fibrillatory rhythms.

scholarly journals Myocardial Mapping in Systemic Sarcoidosis: A Comparison of Two Measurement Approaches

2020 ◽  
Vol 193 (01) ◽  
pp. 68-76
Author(s):  
Darius Dabir ◽  
Julian Luetkens ◽  
Daniel Kuetting ◽  
Jennifer Nadal ◽  
Hans Heinz Schild ◽  
...  
Keyword(s):  
T1 Mapping ◽  
Tissue Characterization ◽  
Cardiac Involvement ◽  
T2 Mapping ◽  
Relaxation Times ◽  
Short Axis Slice ◽  
T2 Relaxation ◽  
Standard Mapping ◽  
Systemic Sarcoidosis ◽  
T1 And T2

Purpose To investigate if T1 and T2 mapping is able to differentiate between diseased and healthy myocardium in patients with systemic sarcoidosis, and to compare the standard mapping measurement (measurement within the whole myocardium of the midventricular short axis slice, SAX) to a more standardized method measuring relaxation times within the midventricular septum (ConSept). Materials and Methods 24 patients with biopsy-proven extracardiac sarcoidosis and 17 healthy control subjects were prospectively enrolled in this study and underwent CMR imaging at 1.5 T including native T1 and T2 mapping. Patients were divided into patients with (LGE+) and without (LGE–) cardiac sarcoidosis. T1 and T2 relaxation times were compared between patients and controls. Furthermore, the SAX and the ConSept approach were compared regarding differentiation between healthy and diseased myocardium. Results T1 and T2 relaxation times were significantly longer in all patients compared with controls using both the SAX and the ConSept approach (p < 0.05). However, LGE+ and LGE– patients showed no significant differences in T1 and T2 relaxation times regardless of the measurement approach used (ConSept/SAX) (p > 0.05). Direct comparison of ConSept and SAX T1 mapping showed high conformity in the discrimination between healthy and diseased myocardium (Kappa = 0.844). Conclusion T1 and T2 mapping may not only enable noninvasive recognition of cardiac involvement in patients with systemic sarcoidosis but may also serve as a marker for early cardiac involvement of the disease allowing for timely treatment. ConSept T1 mapping represents an equivalent method for tissue characterization in this population compared to the SAX approach. Further studies including follow-up examinations are necessary to confirm these preliminary results. Key Points:  Citation Format

Quasienergy integrals for the “standard mapping”

1985 ◽  
Vol 112 (6-7) ◽  
pp. 254-258 ◽  
Author(s):  
F.M. Izrailev ◽  
V.V. Sokolov
Keyword(s):  
Standard Mapping

scholarly journals Cognitive zonal fusion biopsy of the prostate: Original technique between target and saturation

2016 ◽  
Vol 88 (4) ◽  
pp. 292 ◽  
Author(s):  
Andrea B. Galosi ◽  
Guevar Maselli ◽  
Giulia Sbrollini ◽  
Gaetano Donatelli ◽  
Lorenzo Montesi ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Transrectal Ultrasound ◽  
Region Of Interest ◽  
High Grade ◽  
Cognitive Fusion ◽  
Fusion Biopsy ◽  
Fusion Technique ◽  
Saturation Biopsy ◽  
Standard Mapping ◽  
Clinically Significant

We describe our experience in prostate biopsy using a new standardized cognitive fusion techniques, that we call “cognitive zonal fusion biopsy”. This new technique is based on two operative options: the first based on target biopsies, the Cognitive Target Biopsy (CTB) if the same target was detected with transrectal ultrasound (TRUS) and multiparametric magnetic resonance (mpMRI); the second based on saturation biopsies, the Zonal Saturation Biopsy (ZSB) on anatomical zone/s containing the region of interest if the same target was not evident with TRUS and MRI. We evaluated results of our technique compared to standard biopsy in order to identify clinically relevant prostate cancer. Methods: This is a single-center prospective study conducted in 58 pts: 25 biopsy-naïve, 25 with previous negative biopsy and in 8 with cancer in active surveillance. Based on mpMRI and transrectal ultrasonography (TRUS), all patients were scheduled for standard 12-core TRUS-guided biopsy. If mpMRI was suggestive or positive (PI-RADS 3, 4 or 5): patients underwent additional targeted 2 to 6 cores using cognitive zonal fusion technique. Results: 31/58 (53.4%) patients had a cancer. Our technique detected 80.6% (25 of 31) with clinically significant prostate cancer, leading to detection of insignificant cancer in 20%. Using standard mapping in MR negative areas we found 5 clinically significant cancer and 4 not significant cancers. MRI cancer detection rate was 18/31 (58.1%), and 9/18 (50%) in high grade tumors. Therefore MRI missed 50% of high grade cancers. The mean number of cores taken with cognitive zonal fusion biopsy was 6.1 (2-17), in addition biopsy sampling was done outside the ROI areas. Overall 15.4 cores (12-22) were taken. Cancer amount in Zonal Biopsy was larger than 7.3 mm (1-54.5) in comparison with 5.2 mm (1-23.5) in standard mapping. Largest percentage of cancer involvement with cognitive zonal fusion technique was detected in 19.4% vs 15.9%. Conclusions: Cognitive Zonal Saturation Biopsies should be used to reduce operator variability of cognitive fusion biopsy in addition to standard biopsy. Cognitive zonal biopsy based on mpMRI findings identifies clinically relevant prostate in 80%, has larger cancer extension in fusion biopsies than in random biopsies, and reduce the number of cores if compared to saturation biopsy.

Orthomosaics of Historical Aerial Photographs and Horizontal Accuracy Analysis

2020 ◽  
Author(s):  
Ji Won Suh ◽  
William Ouimet
Keyword(s):  
Image Processing ◽  
Aerial Photographs ◽  
Control Points ◽  
Limited Information ◽  
Aerial Photos ◽  
Ground Control Points ◽  
Multiple Datasets ◽  
Standard Mapping ◽  
Lidar Dem ◽  
Air Photo

&lt;p&gt;Orthomosaics from aerial photographs play a pivotal role in understanding land-use/land cover in broad area and the advent of image processing technology allows us to produce orthoimagery. However, recent advanced technologies are seldom applied to produce historical orthophotos from early or mid 20C old aerial photos in broad extent since they have limited information (e.g. camera position, flying altitude, and yaw) which is critical information for orthomosaics. In this context, this study aims to orthomosaic and georectify historical aerial photographs and validate the horizontal accuracy of orthomosacicked outputs. In order to achieve this, firstly, we collected 117 aerial photographs of 1934 (scale 1:12,000) and 68 of 1951 (scale 1:20,000) from UConn air photo achieve focused on Woodstock town in Connecticut, USA. Secondly, we created GCPs (Ground Control Points) as referenced points where they have not changed over time by overlaying multiple datasets such as LiDAR DEM, hillshade map, recent orthoimagery. Thirdly, we align photos with Control Points (CPs), build a mesh, and build orthomosaics of 1934 and 1951, respectively, using Agisoft Photoscan 1.5. Lastly, calculating RMSE (Root Mean Square Error) and offsets comparing between set of GCPs and CPs from Lidar DEM and set of them digitized from orthomosaics. As a result, RMSE values of GCPs and CPs between 1934 and 1951 mostly show that output of this work is acceptable to use for standard mapping and GIS work or visualization based on ASPRS 1990 horizonal accuracy standard. In addition, we found several factors affect horizontal accuracy of orthomosaics; resolution of aerial photos, spatial distribution of GCPs and CPs, the number of CPs and GCPs, the percentage of lateral overlapping area along flight strips, and margin area. Overall, applying automated orthomosaicking image processing to historical aerial photographs has the potential to represent historical landscape and even detect its change in broad extent.&lt;/p&gt;

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