The Experts below are selected from a list of 222 Experts worldwide ranked by ideXlab platform
Tristan Allouis - One of the best experts on this subject based on the ideXlab platform.
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A sequential iterative Dual-Filter for Lidar terrain modeling optimized for complex forested environments
Computers & Geosciences, 2012Co-Authors: Cédric Véga, Sylvie Durrieu, Jules Morel, Tristan AllouisAbstract:This paper introduces a sequential iterative Dual-Filter method for Filtering Lidar point clouds acquired over rough and forested terrain and computing a digital terrain model (DTM). The method belongs to the family of virtual deforestation algorithms that iteratively detect and Filter objects above-the ground surface. The method uses both points and raster models to do so. The algorithm performance was first tested over a complex badlands environment and compared to a reference model obtained using a traditional TIN-Iterative approach. It was further tested on a benchmark site of the ISPRS (site 5) representing mainly forests and slopes. Over badlands, the resulting DTM elevation RMSE was 0.14m over flat areas, and increased to 0.28m under forested and rough terrain. The later value was 12.5% lower than the one obtained with a TIN-Iterative approach. Over the ISPRS site, the TIN-Iterative model provided better results for 3 out of the 4 sample sites. But the proposed algorithm, still worked fairly well provided a total classification error of 5.52%, and is well ranked compared with other algorithms. While the TIN-iterative approach might work better with low density, the proposed one is a good alternative to process high density point cloud and compute DTMs suitable for modeling either hydrodynamic or morphological processes under forest cover at a local scale.
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A sequential iterative Dual-Filter for Lidar terrain modeling opticomplex forested environmentsmized for complex forested environments
Computers & Geosciences, 2012Co-Authors: Cédric Véga, Sylvie Durrieu, Jules Morel, Tristan AllouisAbstract:This paper introduces a sequential iterative Dual-Filter method for Filtering Lidar point clouds acquired over rough and forested terrain and computing a digital terrain model (DTM). The method belongs to the family of virtual deforestation algorithms that iteratively detect and Filter objects above-the ground surface. The method uses both points and raster models to do so. The algorithm performance was first tested over a complex badlands environment and compared to a reference model obtained using a traditional TIN-Iterative approach. It was further tested on a benchmark site of the ISPRS (site 5) representing mainly forests and slopes. Over badlands, the resulting DTM elevation RMSE was 0.14 m over flat areas, and increased to 0.28 m under forested and rough terrain. The later value was 12.5% lower than the one obtained with a TIN-Iterative approach. Over the ISPRS site, the TIN-Iterative model provided better results for 3 out of the 4 sample sites. But the proposed algorithm, still worked fairly well provided a total classification error of 5.52%, and is well ranked compared with other algorithms. While the TIN-iterative approach might work better with low density, the proposed one is a good alternative to process high density point cloud and compute DTMs suitable for modeling either hydrodynamic or morphological processes under forest cover at a local scale. (C) 2012 Elsevier Ltd. All rights reserved.
Cédric Véga - One of the best experts on this subject based on the ideXlab platform.
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A sequential iterative Dual-Filter for Lidar terrain modeling optimized for complex forested environments
Computers & Geosciences, 2012Co-Authors: Cédric Véga, Sylvie Durrieu, Jules Morel, Tristan AllouisAbstract:This paper introduces a sequential iterative Dual-Filter method for Filtering Lidar point clouds acquired over rough and forested terrain and computing a digital terrain model (DTM). The method belongs to the family of virtual deforestation algorithms that iteratively detect and Filter objects above-the ground surface. The method uses both points and raster models to do so. The algorithm performance was first tested over a complex badlands environment and compared to a reference model obtained using a traditional TIN-Iterative approach. It was further tested on a benchmark site of the ISPRS (site 5) representing mainly forests and slopes. Over badlands, the resulting DTM elevation RMSE was 0.14m over flat areas, and increased to 0.28m under forested and rough terrain. The later value was 12.5% lower than the one obtained with a TIN-Iterative approach. Over the ISPRS site, the TIN-Iterative model provided better results for 3 out of the 4 sample sites. But the proposed algorithm, still worked fairly well provided a total classification error of 5.52%, and is well ranked compared with other algorithms. While the TIN-iterative approach might work better with low density, the proposed one is a good alternative to process high density point cloud and compute DTMs suitable for modeling either hydrodynamic or morphological processes under forest cover at a local scale.
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A sequential iterative Dual-Filter for Lidar terrain modeling opticomplex forested environmentsmized for complex forested environments
Computers & Geosciences, 2012Co-Authors: Cédric Véga, Sylvie Durrieu, Jules Morel, Tristan AllouisAbstract:This paper introduces a sequential iterative Dual-Filter method for Filtering Lidar point clouds acquired over rough and forested terrain and computing a digital terrain model (DTM). The method belongs to the family of virtual deforestation algorithms that iteratively detect and Filter objects above-the ground surface. The method uses both points and raster models to do so. The algorithm performance was first tested over a complex badlands environment and compared to a reference model obtained using a traditional TIN-Iterative approach. It was further tested on a benchmark site of the ISPRS (site 5) representing mainly forests and slopes. Over badlands, the resulting DTM elevation RMSE was 0.14 m over flat areas, and increased to 0.28 m under forested and rough terrain. The later value was 12.5% lower than the one obtained with a TIN-Iterative approach. Over the ISPRS site, the TIN-Iterative model provided better results for 3 out of the 4 sample sites. But the proposed algorithm, still worked fairly well provided a total classification error of 5.52%, and is well ranked compared with other algorithms. While the TIN-iterative approach might work better with low density, the proposed one is a good alternative to process high density point cloud and compute DTMs suitable for modeling either hydrodynamic or morphological processes under forest cover at a local scale. (C) 2012 Elsevier Ltd. All rights reserved.
Nicolas M. Van Mieghem - One of the best experts on this subject based on the ideXlab platform.
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TCT-754 Predictors For Tissue Embolization During Transcatheter Aortic Valve Implantation
Journal of the American College of Cardiology, 2014Co-Authors: Nicolas M. Van Mieghem, Peter De JaegereAbstract:Cerebrovascular embolization is frequent during Transcatheter Aortic Valve Implantation (TAVI). The aim of this study was to identify variables associated with tissue embolization during TAVI. A total of 82 patients underwent TAVI with a Dual Filter– based embolic protection device (Montage Dual
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Histopathology of Embolic Debris Captured During Transcatheter Aortic Valve Replacement
Circulation, 2013Co-Authors: Nicolas M. Van Mieghem, Marguerite E.i. Schipper, Elena Ladich, Elham Faqiri, Robert M.a. Van Der Boon, Abas Randjgari, Carl Schultz, Adriaan Moelker, Robert Jan Van Geuns, Fumiyuki OtsukaAbstract:Background—Recent transcatheter aortic valve replacement studies have raised concerns about adverse cerebrovascular events. The etiopathology of the embolized material is currently unknown. Methods and Results—A total of 40 patients underwent transcatheter aortic valve replacement with the use of a Dual Filter–based embolic protection device (Montage Dual Filter System, Claret Medical, Inc). Macroscopic material liberated during the transcatheter aortic valve replacement procedure was captured in the device Filter baskets in 30 (75%) patients and sent for histopathologic analysis. The captured material varied in size from 0.15 to 4.0 mm. Amorphous calcified material (size, 0.55–1.8 mm) was identified in 5 patients (17%). In 8 patients (27%), the captured material (size, 0.25–4.0 mm) contained valve tissue composed of loose connective tissue (collagen and elastic fibers) with focal areas of myxoid stroma, with or without coverage by endothelial cells and intermixed with fibrin. In another 13 (43%) patients...
Jochen Wöhrle - One of the best experts on this subject based on the ideXlab platform.
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Rate of peri-procedural stroke observed with cerebral embolic protection during transcatheter aortic valve replacement: a patient-level propensity-matched analysis
European Heart Journal, 2018Co-Authors: Julia Seeger, Raj Makkar, Wolfgang Rottbauer, Jochen Wöhrle, Samir R. Kapadia, Susheel Kodali, Axel Linke, Stephan Haussig, Roxana Mehran, Martin B. LeonAbstract:Aims The role of cerebral embolic protection (CEP) in transcatheter aortic valve replacement (TAVR) remains controversial. Randomized trials have not been powered to demonstrate a reduction in stroke rates. The aim of this patient level pooled analysis was to validate the impact of the Dual-Filter CEP device (Claret Medical Inc., CA, USA) on peri-procedural stroke in a large number of TAVR patients. Methods and results Patients from the SENTINEL US IDE trial were combined with the CLEAN-TAVI and SENTINEL-Ulm study in a patient level pooled analysis (N = 1306). Propensity score matching was performed to adjust for possible confounders. The primary endpoint was procedural stroke within 72 h post-TAVR according to Valve Academic Research Consortium-2 criteria. The secondary endpoint was the combination of all-cause mortality or all-stroke within 72 h after TAVR. In the propensity-matched population, 533 patients underwent TAVR without CEP and 533 patients underwent TAVR with CEP. TAVR patients without vs. with CEP were similar with respect to baseline characteristics, procedural approach, or valve type. In patients undergoing TAVR with Dual-Filter CEP, procedural all-stroke was significantly lower compared with unprotected procedures [1.88% vs. 5.44%, odds ratio 0.35, 95% confidence interval (CI) 0.17-0.72, relative risk reduction 65%, P = 0.0028]. In addition, all-cause mortality and all-stroke were significantly lower (2.06% vs. 6.00%, odds ratio 0.34, 95% CI 0.17-0.68, relative risk reduction 66%, P = 0.0013). Conclusion Our findings suggest that TAVR with the Dual-Filter CEP device is associated with a significant lower rate of peri-procedural stroke compared with unprotected procedures. However, randomized trials are still needed to clarify this issue.
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Significant Differences in Debris Captured by the Sentinel Dual-Filter Cerebral Embolic Protection During Transcatheter Aortic Valve Replacement Among Different Valve Types.
Jacc-cardiovascular Interventions, 2018Co-Authors: Julia Seeger, Renu Virmani, Maria Romero, Birgid Gonska, Wolfgang Rottbauer, Jochen WöhrleAbstract:Abstract Objectives The aim of this study was to evaluate the debris captured by the Claret Sentinel cerebral embolic Dual-Filter protection device during transfemoral transcatheter aortic valve replacement (TAVR) with different valve types. Background Risk for embolization of debris during TAVR may vary by TAVR device. Methods The Filters of 100 consecutive patients were collected and captured debris was analyzed by histopathology and histomorphometry. Three valve types were implanted: the balloon-expandable Edwards SAPIEN 3 (n = 42), the self-expandable Medtronic Evolut R (n = 35), and the mechanically implantable Boston Scientific Lotus (n = 23). Results Among the 3 groups there was no difference in baseline data, including Society of Thoracic Surgeons score for mortality, calcification, or pre-dilation. The type of captured debris did not differ among the 3 valve types in the proximal or distal Filter. With the balloon-expandable valve, there were significantly more patients with large debris measuring ≥1,000 μm. The number of particles in the proximal Filter was significantly lower with the Lotus (89.8 ± 106.3) compared with the Evolut R (187.3 ± 176.9) and Edwards SAPIEN 3 (172.3 ± 133.5) valves (p = 0.035). Total tissue area in the proximal Filter was significantly smaller for the Lotus compared with the other 2 valve types (7.1 ± 6.3, 20.1 ± 19.0, and 21.3 ± 15.1 mm2; p = 0.0014). In contrast, for the distal Filter, there were no differences with respect to valve type for total tissue area, particle size, and number of particles. Conclusions A significant difference was observed in the size and number of captured tissue particles with the double-Filter embolic protection device among different valve types in patients undergoing TAVR. The largest particles were observed in patients treated with a balloon-expandable valve.
Fumiyuki Otsuka - One of the best experts on this subject based on the ideXlab platform.
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Histopathology of Embolic Debris Captured During Transcatheter Aortic Valve Replacement
Circulation, 2013Co-Authors: Nicolas M. Van Mieghem, Marguerite E.i. Schipper, Elena Ladich, Elham Faqiri, Robert M.a. Van Der Boon, Abas Randjgari, Carl Schultz, Adriaan Moelker, Robert Jan Van Geuns, Fumiyuki OtsukaAbstract:Background—Recent transcatheter aortic valve replacement studies have raised concerns about adverse cerebrovascular events. The etiopathology of the embolized material is currently unknown. Methods and Results—A total of 40 patients underwent transcatheter aortic valve replacement with the use of a Dual Filter–based embolic protection device (Montage Dual Filter System, Claret Medical, Inc). Macroscopic material liberated during the transcatheter aortic valve replacement procedure was captured in the device Filter baskets in 30 (75%) patients and sent for histopathologic analysis. The captured material varied in size from 0.15 to 4.0 mm. Amorphous calcified material (size, 0.55–1.8 mm) was identified in 5 patients (17%). In 8 patients (27%), the captured material (size, 0.25–4.0 mm) contained valve tissue composed of loose connective tissue (collagen and elastic fibers) with focal areas of myxoid stroma, with or without coverage by endothelial cells and intermixed with fibrin. In another 13 (43%) patients...
