Simulating Developmental Cardiac Morphology in Virtual Reality Using a Deformable Image Registration Approach

Abiri, Arash; Ding, Yichen; Abiri, Parinaz; Packard, René R. Sevag; Vedula, Vijay; Marsden, Alison; Kuo, C.-C. Jay; Hsiai, Tzung K.

doi:10.1007/s10439-018-02113-z

Cited by 14 publications

(13 citation statements)

References 70 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The application of Saak transform to segment 3-D LSFM-acquired images creates an opportunity to investigate chemotherapyinduced cardiac structure and mechanics. Previously, we needed to perform manual or semi-automated segmentation to reconstruct LSFM architectures for computational fluid dynamics [15,16] and interactive virtual reality [17,18]. The addition of edge detection to Saak transform enables the calculation of surface area in relation to the volume of myocardium.…”

Section: Discussionmentioning

confidence: 99%

“…Light-sheet fluorescence microscopy (LSFM) is instrumental in advancing the field of developmental biology and tissue regeneration [1][2][3][4]. LSFM systems have the capacity to investigate cardiac ultra-structure and function [5][6][7][8][9][10][11][12][13][14], providing the moving Baek, Zhaoqiang Wang, Mehrdad Roustaei, Dengfeng Kuang, C.-C. Jay Kuo †, and Tzung K. Hsiai † boundary conditions for computational fluid dynamics [15,16] and the specific labeling of trabecular network for interactive virtual reality [17,18]. However, efficient and robust structural segmentation of cardiac trabeculation remains a post-imaging challenge [19][20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Saak Transform-Based Machine Learning for Light-Sheet Imaging of Cardiac Trabeculation

Ding

Gudapati

Lin

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

AbstractRecent advances in light-sheet fluorescence microscopy (LSFM) enable 3-dimensional (3-D) imaging of cardiac architecture and mechanics in toto. However, segmentation of the cardiac trabecular network to quantify cardiac injury remains a challenge. We hereby employed “subspace approximation with augmented kernels (Saak) transform” for accurate and efficient quantification of the light-sheet image stacks following chemotherapy-treatment. We established a machine learning framework with augmented kernels based on the Karhunen-Loeve Transform (KLT) to preserve linearity and reversibility of rectification. The Saak transform-based machine learning enhances computational efficiency and obviates iterative optimization of cost function needed for neural networks, minimizing the number of training data sets to three 2-D slices for segmentation in our scenario. The integration of forward and inverse Saak transforms serves as a light-weight module to filter adversarial perturbations and reconstruct estimated images, salvaging robustness of existing classification methods. The accuracy and robustness of the Saak transform are evident following the tests of dice similarity coefficients and various adversary perturbation algorithms, respectively. The addition of edge detection further allows for quantifying the surface area to volume ratio (SVR) of the myocardium in response to chemotherapy-induced cardiac remodeling. The combination of Saak transform, random forest, and edge detection augments segmentation efficiency by 20-fold as compared to manual processing; thus, establishing a robust framework for post light-sheet imaging processing, creating a data-driven machine learning for 3-D quantification of cardiac ultra-structure.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Saak Transform-Based Machine Learning for Light-Sheet Imaging of Cardiac Trabeculation

Ding

Gudapati

Lin

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…-Internet of Things (IoT), studied by Ansari et al (2018), Mendoza and Kleinschmidt et al (2018); -Blockchain (Li et al, 2018;Ma et al, 2018); -The technology of processing Big Data allows for automatisation of processing vast arrays of digital information (e.g., Kumar et al, 2018;Kumari et al (2018); -Unmanned flying vehicles and manipulatorsremotely controlled mechanismsare investigated by Dehghani and Menhaj (2018) and Song et al (2018); -Robototronics (Jaikaew et al, 2018;Shafei and Shafei, 2018); -Virtual and alternate (Abiri et al, 2018;de-Juan-Ripoll et al, 2018); -The technology of 3D print (Abiri et al, 2018;de-Juan-Ripoll et al, 2018;Dickinson, 2018). -Artificial intelligence (AI) (Galloway and Swiatek, 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

Towards a ‘wide’ role for venture capital in OECD countries' industry 4.0

Sergi

Popkova

2022

Heliyon

View full text Add to dashboard Cite

This paper focuses on the current theoretical views of venture capital that predetermines a "narrow" treatment. In the light of the existing "narrow" treatment, venture investors seek private commercial interests in financial support for Industry 4.0, ignoring other interests that fall beyond the limits of the current "narrow" treatment of venture capital. A "wide" treatment of venture capital 4.0 proposed in this paper allows for improving venture investors' market strategies. Implementing this treatment, they will strive for providing a whole range of advantages for society. Due to this novel approach, venture capital 4.0 might become a tool of corporate social responsibility. To substantiate this novel approach, this paper considers data for 2020 that reflect the influence of venture capital 4.0 on the economy in the period of its stability for 33 countries of the OECD, including developed and developing countries. Econometric modelling based on the official statistics data proves that Industry 4.0 venture capital will help achieve such growth goals as innovative development, global competitiveness, and increasing digital competitiveness. The limitations of this research are due to the impossibility of achieving such goals as sustainable development, economic growth, and implementation of human potential; what's more, the specifics of developing countries have not been studied sufficiently. The conclusions are oriented mainly at developed countries and could merely partially be applied to developing countries. During further research, it is expedient to exploremore thoroughlythe experience of the influence of Industry 4.0 venture capital on emerging economies.

show abstract

“…These markers served as representative landmarks of the surface of the phantom that would have the greatest contact with the epicardium. As previously described [46], deformable image registration (DIR) was applied on each time point of the 4-D thoracic MRI to generate 3-D displacement fields that represented the instantaneous cardiac motion at discrete time points in the cardiac cycle. To simulate the moving phantom at any given time point, the 3-D phantom image of the previous time point was transformed using the 3-D displacement field that was calculated for the given time point.…”

Section: Simulating Pacing Function Across a Cardiac Cyclementioning

confidence: 99%

A Multi-Dimensional Analysis of a Novel Approach for Wireless Stimulation

Abiri

Yousefi

Abiri

et al. 2020

IEEE Trans. Biomed. Eng.

Self Cite

View full text Add to dashboard Cite

The elimination of integrated batteries in biomedical implants holds great promise for improving health outcomes in patients with implantable devices. However, despite extensive research in wireless power transfer, achieving efficient power transfer and effective operational range have remained a hindering challenge within anatomical constraints. Objective: We hereby demonstrate an intravascular wireless and batteryless microscale stimulator, designed for (1) low power dissipation via intermittent transmission and (2) reduced fixation mechanical burden via deployment to the anterior cardiac vein (ACV, ~3.8 mm in diameter). Methods: We introduced a unique coil design circumferentially confined to a 3 mm diameter hollow-cylinder that was driven by a novel transmitter-based control architecture with improved power efficiency. Results: We examined wireless capacity using heterogenous bovine tissue, demonstrating >5 V stimulation threshold with up to 20 mm transmitter-receiver displacement and 20 o of misalignment. Feasibility for human use was validated using Finite Element Method (FEM) simulation of the cardiac cycle, guided by pacer phantom-integrated Magnetic Resonance Images (MRI). Conclusion: This system design thus enabled sufficient wireless power transfer in the face of extensive stimulator miniaturization. Significance: Our successful feasibility studies demonstrated the capacity for minimally invasive deployment and low-risk fixation. Index Terms-wireless medical devices, wireless pacemaker, inductive power transfer, implantable medical devices, implantable cardiovascular devices I. INTRODUCTION MPLANTABLE stimulators, including cardiac pacemakers and neuromodulation devices used for spinal cord, deep brain, and peripheral nerve stimulation, demand the use of device leads for the transmission of power from the pulse generator to the stimulation electrodes. Despite their extensive use, implanted leads can result in a variety of medical complications.

show abstract

Simulating Developmental Cardiac Morphology in Virtual Reality Using a Deformable Image Registration Approach

Cited by 14 publications

References 70 publications

Saak Transform-Based Machine Learning for Light-Sheet Imaging of Cardiac Trabeculation

Saak Transform-Based Machine Learning for Light-Sheet Imaging of Cardiac Trabeculation

Towards a ‘wide’ role for venture capital in OECD countries' industry 4.0

A Multi-Dimensional Analysis of a Novel Approach for Wireless Stimulation

Contact Info

Product

Resources

About