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Wang C, Karl R, Sharan L, Grizelj A, Fischer S, Karck M, De Simone R, Romano G, Engelhardt S. Surgical training of minimally invasive mitral valve repair on a patient-specific simulator improves surgical skills. Eur J Cardiothorac Surg 2024; 65:ezad387. [PMID: 37988128 DOI: 10.1093/ejcts/ezad387] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 10/05/2023] [Accepted: 11/20/2023] [Indexed: 11/22/2023] Open
Abstract
OBJECTIVES Minimally invasive mitral valve repair (MVR) is considered one of the most challenging operations in cardiac surgery and requires much practice and experience. Simulation-based surgical training might be a method to support the learning process and help to flatten the steep learning curve of novices. The purpose of this study was to show the possible effects on learning of surgical training using a high-fidelity simulator with patient-specific mitral valve replicas. METHODS Twenty-five participants were recruited to perform MVR on anatomically realistic valve models during different training sessions. After every session their performance was evaluated by a surgical expert regarding accuracy and duration for each step. A second blinded rater similarly assessed the performance after the study. Through repeated documentation of those parameters, their progress in learning was analysed, and gains in proficiency were evaluated. RESULTS Participants showed significant performance enhancements in terms of both accuracy and time. Their surgical skills showed sizeable improvements after only 1 session. For example, the time to implant neo-chordae decreased by 24.64% (354 s-264 s, P < 0.001) and the time for annuloplasty by 4.01% (54 s-50 s, P = 0.165), whereas the number of irregular stitches for annuloplasty decreased from 52% to 24%.The significance of simulation-based surgical training as a tool for acquiring and training surgical skills was reviewed positively. CONCLUSIONS The results of this study indicate that simulation-based surgical training is a valuable and effective method for learning reconstructive techniques of minimally invasive MVR and overall general dexterity.The novel learning and training options should be implemented in the surgical traineeship for systematic teaching of various surgical skills.
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Affiliation(s)
- Christina Wang
- University Hospital Heidelberg, Department of Cardiac Surgery, Heidelberg, Germany
| | - Roger Karl
- University Hospital Heidelberg, Department of Cardiac Surgery, Heidelberg, Germany
- University Hospital Heidelberg, Department of Internal Medicine III, Heidelberg, Germany
| | - Lalith Sharan
- University Hospital Heidelberg, Department of Cardiac Surgery, Heidelberg, Germany
- University Hospital Heidelberg, Department of Internal Medicine III, Heidelberg, Germany
| | - Andela Grizelj
- University Hospital Heidelberg, Department of Cardiac Surgery, Heidelberg, Germany
| | - Samantha Fischer
- University Hospital Heidelberg, Department of Cardiac Surgery, Heidelberg, Germany
| | - Matthias Karck
- University Hospital Heidelberg, Department of Cardiac Surgery, Heidelberg, Germany
| | - Raffaele De Simone
- University Hospital Heidelberg, Department of Cardiac Surgery, Heidelberg, Germany
| | - Gabriele Romano
- University Hospital Heidelberg, Department of Cardiac Surgery, Heidelberg, Germany
| | - Sandy Engelhardt
- University Hospital Heidelberg, Department of Cardiac Surgery, Heidelberg, Germany
- University Hospital Heidelberg, Department of Internal Medicine III, Heidelberg, Germany
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Kostiuchik G, Sharan L, Mayer B, Wolf I, Preim B, Engelhardt S. Surgical phase and instrument recognition: how to identify appropriate dataset splits. Int J Comput Assist Radiol Surg 2024:10.1007/s11548-024-03063-9. [PMID: 38285380 DOI: 10.1007/s11548-024-03063-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 01/08/2024] [Indexed: 01/30/2024]
Abstract
PURPOSE Machine learning approaches can only be reliably evaluated if training, validation, and test data splits are representative and not affected by the absence of classes. Surgical workflow and instrument recognition are two tasks that are complicated in this manner, because of heavy data imbalances resulting from different length of phases and their potential erratic occurrences. Furthermore, sub-properties like instrument (co-)occurrence are usually not particularly considered when defining the split. METHODS We present a publicly available data visualization tool that enables interactive exploration of dataset partitions for surgical phase and instrument recognition. The application focuses on the visualization of the occurrence of phases, phase transitions, instruments, and instrument combinations across sets. Particularly, it facilitates assessment of dataset splits, especially regarding identification of sub-optimal dataset splits. RESULTS We performed analysis of the datasets Cholec80, CATARACTS, CaDIS, M2CAI-workflow, and M2CAI-tool using the proposed application. We were able to uncover phase transitions, individual instruments, and combinations of surgical instruments that were not represented in one of the sets. Addressing these issues, we identify possible improvements in the splits using our tool. A user study with ten participants demonstrated that the participants were able to successfully solve a selection of data exploration tasks. CONCLUSION In highly unbalanced class distributions, special care should be taken with respect to the selection of an appropriate dataset split because it can greatly influence the assessments of machine learning approaches. Our interactive tool allows for determination of better splits to improve current practices in the field. The live application is available at https://cardio-ai.github.io/endovis-ml/ .
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Affiliation(s)
- Georgii Kostiuchik
- Department of Cardiac Surgery, Heidelberg University Hospital, Heidelberg, Germany.
- DZHK (German Centre for Cardiovascular Research), Partner Site Heidelberg/Mannheim, Heidelberg, Germany.
| | - Lalith Sharan
- Department of Cardiac Surgery, Heidelberg University Hospital, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Heidelberg/Mannheim, Heidelberg, Germany
| | - Benedikt Mayer
- Department of Simulation and Graphics, University of Magdeburg, Magdeburg, Germany
| | - Ivo Wolf
- Department of Computer Science, Mannheim University of Applied Sciences, Mannheim, Germany
| | - Bernhard Preim
- Department of Simulation and Graphics, University of Magdeburg, Magdeburg, Germany
| | - Sandy Engelhardt
- Department of Cardiac Surgery, Heidelberg University Hospital, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Heidelberg/Mannheim, Heidelberg, Germany
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Burger L, Sharan L, Karl R, Wang C, Karck M, De Simone R, Wolf I, Romano G, Engelhardt S. Comparative evaluation of three commercially available markerless depth sensors for close-range use in surgical simulation. Int J Comput Assist Radiol Surg 2023:10.1007/s11548-023-02887-1. [PMID: 37140737 DOI: 10.1007/s11548-023-02887-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 03/27/2023] [Indexed: 05/05/2023]
Abstract
PURPOSE Minimally invasive surgeries have restricted surgical ports, demanding a high skill level from the surgeon. Surgical simulation potentially reduces this steep learning curve and additionally provides quantitative feedback. Markerless depth sensors show great promise for quantification, but most such sensors are not designed for accurate reconstruction of complex anatomical forms in close-range. METHODS This work compares three commercially available depth sensors, namely the Intel D405, D415, and the Stereolabs Zed-Mini in the range of 12-20 cm, for use in surgical simulation. Three environments are designed that closely mimic surgical simulation, comprising planar surfaces, rigid objects, and mitral valve models of silicone and realistic porcine tissue. The cameras are evaluated on Z-accuracy, temporal noise, fill rate, checker distance, point cloud comparisons, and visual inspection of surgical scenes, across several camera settings. RESULTS The Intel cameras show sub-mm accuracy in most static environments. The D415 fails in reconstructing valve models, while the Zed-Mini provides lesser temporal noise and higher fill rate. The D405 could reconstruct anatomical structures like the mitral valve leaflet and a ring prosthesis, but performs poorly for reflective surfaces like surgical tools and thin structures like sutures. CONCLUSION If a high temporal resolution is needed and lower spatial resolution is acceptable, the Zed-Mini is the best choice, whereas the Intel D405 is the most suited for close-range applications. The D405 shows potential for applications like deformable registration of surfaces, but is not yet suitable for applications like real-time tool tracking or surgical skill assessment.
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Affiliation(s)
- Lukas Burger
- Department of Cardiac Surgery, Heidelberg University Hospital, Heidelberg, Germany
- Department of Computer Science, Mannheim University of Applied Sciences, Mannheim, Germany
| | - Lalith Sharan
- Department of Cardiac Surgery, Heidelberg University Hospital, Heidelberg, Germany.
- DZHK (German Centre for Cardiovascular Research), Heidelberg, Germany.
| | - Roger Karl
- Department of Cardiac Surgery, Heidelberg University Hospital, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research), Heidelberg, Germany
| | - Christina Wang
- Department of Cardiac Surgery, Heidelberg University Hospital, Heidelberg, Germany
| | - Matthias Karck
- Department of Cardiac Surgery, Heidelberg University Hospital, Heidelberg, Germany
| | - Raffaele De Simone
- Department of Cardiac Surgery, Heidelberg University Hospital, Heidelberg, Germany
| | - Ivo Wolf
- Department of Computer Science, Mannheim University of Applied Sciences, Mannheim, Germany
| | - Gabriele Romano
- Department of Cardiac Surgery, Heidelberg University Hospital, Heidelberg, Germany
| | - Sandy Engelhardt
- Department of Cardiac Surgery, Heidelberg University Hospital, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research), Heidelberg, Germany
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Fischer S, Romano G, Sharan L, Warnecke G, Mereles D, Karck M, De Simone R, Engelhardt S. Surgical Rehearsal for Mitral Valve Repair: Personalizing Surgical Simulation by 3D Printing. Ann Thorac Surg 2023; 115:1062-1067. [PMID: 36638948 DOI: 10.1016/j.athoracsur.2022.12.039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Revised: 11/23/2022] [Accepted: 12/14/2022] [Indexed: 01/12/2023]
Abstract
PURPOSE The goal of this study was to show possible effects of performing the actual procedure of mitral valve repair (MVR) on personalized silicone models 1 day before operation. DESCRIPTION Based on preoperative 3-dimensional echocardiography recordings, flexible 3-dimensional replicas of the depicted pathologic mitral valves could be produced and used for a simulation of reconstructive techniques analogous to the upcoming MVR procedure. We integrated this step of personalized surgical planning into the clinical routine of 6 MVR cases with 3 different surgeons. This pilot study was assessed by evaluating questionnaires and by comparing isolated surgical steps with conventional MVRs. EVALUATION This approach was considered a better preparation for MVRs with overall positive responses from the surgeons. Simulation helped reduce the time of initial inspection of the valve because of better understanding of the valve's pathomorphologic features. Annuloplasty benefited from preoperative sizing by reducing the number of sizing attempts. CONCLUSIONS These initial findings suggest that simulation-based surgical planning can be implemented into patients' and physicians' clinical workflow as a major technologic advancement for future MVR preparation.
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Affiliation(s)
- Samantha Fischer
- Department of Cardiac Surgery, University Hospital Heidelberg, Heidelberg, Germany; Informatics for Life Institute, Heidelberg University, Heidelberg, Germany
| | - Gabriele Romano
- Department of Cardiac Surgery, University Hospital Heidelberg, Heidelberg, Germany
| | - Lalith Sharan
- Department of Cardiac Surgery, University Hospital Heidelberg, Heidelberg, Germany; Department of Internal Medicine III, University Hospital Heidelberg, Heidelberg, Germany; Informatics for Life Institute, Heidelberg University, Heidelberg, Germany
| | - Gregor Warnecke
- Department of Cardiac Surgery, University Hospital Heidelberg, Heidelberg, Germany
| | - Derliz Mereles
- Department of Internal Medicine III, University Hospital Heidelberg, Heidelberg, Germany
| | - Matthias Karck
- Department of Cardiac Surgery, University Hospital Heidelberg, Heidelberg, Germany
| | - Raffaele De Simone
- Department of Cardiac Surgery, University Hospital Heidelberg, Heidelberg, Germany; Informatics for Life Institute, Heidelberg University, Heidelberg, Germany
| | - Sandy Engelhardt
- Department of Cardiac Surgery, University Hospital Heidelberg, Heidelberg, Germany; Department of Internal Medicine III, University Hospital Heidelberg, Heidelberg, Germany; Informatics for Life Institute, Heidelberg University, Heidelberg, Germany.
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Sharan L, Kelm H, Romano G, Karck M, De Simone R, Engelhardt S. mvHOTA: A multi-view higher order tracking accuracy metric to measure temporal and spatial associations in multi-point tracking. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization 2022. [DOI: 10.1080/21681163.2022.2159535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Affiliation(s)
- Lalith Sharan
- DZHK (German Centre for Cardiovascular Research), partner site Heidelberg/Mannheim, Germany
| | - Halvar Kelm
- Department of Cardiac Surgery, Heidelberg University Hospital, Heidelberg, Germany
| | - Gabriele Romano
- DZHK (German Centre for Cardiovascular Research), partner site Heidelberg/Mannheim, Germany
| | - Matthias Karck
- Department of Cardiac Surgery, Heidelberg University Hospital, Heidelberg, Germany
| | - Raffaele De Simone
- Department of Cardiac Surgery, Heidelberg University Hospital, Heidelberg, Germany
| | - Sandy Engelhardt
- DZHK (German Centre for Cardiovascular Research), partner site Heidelberg/Mannheim, Germany
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Sharan L, Romano G, Brand J, Kelm H, Karck M, De Simone R, Engelhardt S. Point detection through multi-instance deep heatmap regression for sutures in endoscopy. Int J Comput Assist Radiol Surg 2021; 16:2107-2117. [PMID: 34748152 PMCID: PMC8616891 DOI: 10.1007/s11548-021-02523-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Accepted: 10/18/2021] [Indexed: 11/28/2022]
Abstract
Purpose: Mitral valve repair is a complex minimally invasive surgery of the heart valve. In this context, suture detection from endoscopic images is a highly relevant task that provides quantitative information to analyse suturing patterns, assess prosthetic configurations and produce augmented reality visualisations. Facial or anatomical landmark detection tasks typically contain a fixed number of landmarks, and use regression or fixed heatmap-based approaches to localize the landmarks. However in endoscopy, there are a varying number of sutures in every image, and the sutures may occur at any location in the annulus, as they are not semantically unique.
Method: In this work, we formulate the suture detection task as a multi-instance deep heatmap regression problem, to identify entry and exit points of sutures. We extend our previous work, and introduce the novel use of a 2D Gaussian layer followed by a differentiable 2D spatial Soft-Argmax layer to function as a local non-maximum suppression. Results: We present extensive experiments with multiple heatmap distribution functions and two variants of the proposed model. In the intra-operative domain, Variant 1 showed a mean \documentclass[12pt]{minimal}
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Conclusion: The proposed model shows an improvement over the baseline in the intra-operative and the simulator domains. The data is made publicly available within the scope of the MICCAI AdaptOR2021 Challenge https://adaptor2021.github.io/, and the code at https://github.com/Cardio-AI/suture-detection-pytorch/.
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Affiliation(s)
- Lalith Sharan
- Department of Internal Medicine III, Group Artificial Intelligence in Cardiovascular Medicine, Heidelberg University Hospital, 69120, Heidelberg, Germany.
| | - Gabriele Romano
- Department of Cardiac Surgery, Heidelberg University Hospital, 69120, Heidelberg, Germany
| | - Julian Brand
- Department of Internal Medicine III, Group Artificial Intelligence in Cardiovascular Medicine, Heidelberg University Hospital, 69120, Heidelberg, Germany
| | - Halvar Kelm
- Department of Internal Medicine III, Group Artificial Intelligence in Cardiovascular Medicine, Heidelberg University Hospital, 69120, Heidelberg, Germany
| | - Matthias Karck
- Department of Cardiac Surgery, Heidelberg University Hospital, 69120, Heidelberg, Germany
| | - Raffaele De Simone
- Department of Cardiac Surgery, Heidelberg University Hospital, 69120, Heidelberg, Germany
| | - Sandy Engelhardt
- Department of Internal Medicine III, Group Artificial Intelligence in Cardiovascular Medicine, Heidelberg University Hospital, 69120, Heidelberg, Germany
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Sharan L, Romano G, Koehler S, Kelm H, Karck M, De Simone R, Engelhardt S. Mutually improved endoscopic image synthesis and landmark detection in unpaired image-to-image translation. IEEE J Biomed Health Inform 2021; 26:127-138. [PMID: 34310335 DOI: 10.1109/jbhi.2021.3099858] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The CycleGAN framework allows for unsupervised image-to-image translation of unpaired data. In a scenario of surgical training on a physical surgical simulator, this method can be used to transform endoscopic images of phantoms into images which more closely resemble the intra-operative appearance of the same surgical target structure. This can be viewed as a novel augmented reality approach, which we coined Hyperrealism in previous work. In this use case, it is of paramount importance to display objects like needles, sutures or instruments consistent in both domains while altering the style to a more tissue-like appearance. Segmentation of these objects would allow for a direct transfer, however, contouring of these, partly tiny and thin foreground objects is cumbersome and perhaps inaccurate. Instead, we propose to use landmark detection on the points when sutures pass into the tissue. This objective is directly incorporated into a CycleGAN framework by treating the performance of pre-trained detector models as an additional optimization goal. We show that a task defined on these sparse landmark labels improves consistency of synthesis by the generator network in both domains. Comparing a baseline CycleGAN architecture to our proposed extension (DetCycleGAN), mean precision (PPV) improved by +61.32, mean sensitivity (TPR) by +37.91, and mean F1 score by +0.4743. Furthermore, it could be shown that by dataset fusion, generated intra-operative images can be leveraged as additional training data for the detection network itself. The data is released within the scope of the AdaptOR MICCAI Challenge 2021 at https://adaptor2021.github.io/, and code at https://github.com/Cardio-AI/detcyclegan_pytorch.
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Shapovalenko O, Pavliuchenko O, Furmanova Y, Sharan L, Kuzmin O. IMPROVEMENT OF THE RECIPE COMPOSITION OF SPECIAL-PURPOSE GLUTEN-FREE CHOCOLATE MUFFINS. FST 2020. [DOI: 10.15673/fst.v14i4.1897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
The paper considers how gluten-free flours, in particular, those made from coconuts and brown rice, can be used in the technology of gluten-free chocolate muffins in order to expand the range of special purpose products. Studies by domestic and foreign authors dedicated to using different flour types in today’s gluten-free technologies have been analysed. It has been proved that wheat flour can be fully replaced with gluten-free flour mixtures in the recipe of chocolate muffins. Analysis of the chemical composition of coconut flour has shown its higher fat content, compared with wheat flour, and twice as much protein and dietary fibre (18%). Coconut flour exceeds wheat flour not only in the main macronutrients, but also in the content of the main minerals. Brown rice flour, too, contains more fats and vitamins of the B-group than wheat flour does, and is a source of sodium, magnesium, phosphorus, silicon, and sulphur. It contains up to 80% of starch and, like coconut flour, is gluten-free. Replacing wheat flour in the classical muffin recipe with mixtures of coconut and brown rice flours in the ratios 30:70, 40:60, and 50:50 reduces the moisture content and density of the dough. The moisture content in the finished muffins, too, is lower by 0.7, 1.2, and 1.5% respectively. It has been confirmed that if the gluten-free flour mixture contains over 50% of coconut flour, it reduces the specific volume of resulting muffins and worsens their quality parameters. The Harrington method was used to estimate the comprehensive quality index of the chocolate muffins. This has shown that full substitution of wheat flour for a mixture of gluten- free flours in the ratio 40:60 (coconut flour:brown rice flour) allows achieving the best-balanced sensory characteristics. Gluten-free muffins have a pleasant brown colour of the crust, their crumb is quite soft, homogeneous, and porous, with a balanced taste and an aroma of cocoa combined with light coconut notes.
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Sharan L, Burger L, Kostiuchik G, Wolf I, Karck M, De Simone R, Engelhardt S. Domain gap in adapting self-supervised depth estimation methods for stereo-endoscopy. Current Directions in Biomedical Engineering 2020. [DOI: 10.1515/cdbme-2020-0004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Abstract
In endoscopy, depth estimation is a task that potentially helps in quantifying visual information for better scene understanding. A plethora of depth estimation algorithms have been proposed in the computer vision community. The endoscopic domain however, differs from the typical depth estimation scenario due to differences in the setup and nature of the scene. Furthermore, it is unfeasible to obtain ground truth depth information owing to an unsuitable detection range of off-the-shelf depth sensors and difficulties in setting up a depth-sensor in a surgical environment. In this paper, an existing self-supervised approach, called Monodepth [1], from the field of autonomous driving is applied to a novel dataset of stereo-endoscopic images from reconstructive mitral valve surgery. While it is already known that endoscopic scenes are more challenging than outdoor driving scenes, the paper performs experiments to quantify the comparison, and describe the domain gap and challenges involved in the transfer of these methods.
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Affiliation(s)
- Lalith Sharan
- WG Artificial Intelligence in Cardiovascular Medicine (AICM), University Hospital Heidelberg , Heidelberg , Germany
- Informatics for Life , Heidelberg , Germany
| | - Lukas Burger
- WG Artificial Intelligence in Cardiovascular Medicine (AICM), University Hospital Heidelberg , Heidelberg , Germany
- Department of Computer Science , Mannheim University of Applied Sciences , Mannheim , Germany
| | - Georgii Kostiuchik
- Department of Computer Science , Mannheim University of Applied Sciences , Mannheim , Germany
| | - Ivo Wolf
- Department of Computer Science , Mannheim University of Applied Sciences , Mannheim , Germany
| | - Matthias Karck
- Department of Cardiac Surgery , University Hospital Heidelberg , Heidelberg , Germany
| | - Raffaele De Simone
- Department of Cardiac Surgery , University Hospital Heidelberg , Heidelberg , Germany
| | - Sandy Engelhardt
- WG Artificial Intelligence in Cardiovascular Medicine (AICM), University Hospital Heidelberg , Heidelberg , Germany
- Informatics for Life , Heidelberg , Germany
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Sharan L, Rosenholtz R. If you can see it, you spot it sooner: Peripheral change detection is correlated with performance on `Spot-The-Difference' puzzles. J Vis 2014. [DOI: 10.1167/14.10.615] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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Sharan L, Rosenholtz R. If you cannot see it, you look at it: Visual conspicuity in real-world scenes is correlated with fixations. J Vis 2013. [DOI: 10.1167/13.9.923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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Sharan L, Sigal L, Hodgins J. Recognizing activities and poses: lessons from computer vision. J Vis 2012. [DOI: 10.1167/12.9.645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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Sharan L, Kaemmerer M, Mahler M, Won Sok K, Hodgins J. Animated character appearance does not affect judgments of motion trajectory. J Vis 2011. [DOI: 10.1167/11.11.690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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Sharan L, Liu C, Rosenholtz R, Adelson E. A computational model for material recognition. J Vis 2010. [DOI: 10.1167/10.7.987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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Sharan L, Adelson E, Motoyoshi I, Nishida S. Histogram skewness is useful and easily computed in neural hardware. J Vis 2010. [DOI: 10.1167/7.9.966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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Kamalesh M, Subbiah S, Sharan L, Tawam M, Sawada S. Rapid formation of left atrial appendage thrombus after unsuccessful cardioversion of atrial fibrillation. Echocardiography 2001; 18:157-8. [PMID: 11262539 DOI: 10.1046/j.1540-8175.2001.00157.x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
The acute effect of failed attempts of cardioversion on left atrial (LA) and left atrial appendage (LAA) functions are generally considered benign and no adverse effects have been reported. We report on a subject who had rapid formation of a fresh, mobile thrombus in the LAA despite unsuccessful cardioversion and therapeutic anticoagulation.
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Affiliation(s)
- M Kamalesh
- University of Illinois College of Medicine at Urbana-Champaign, USA.
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