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草榴社区 Webinar Series – Putting AI to Work for Medical Device Development
Improving Clinical Outcomes Through Patient-Specific Design, Surgical Planning and Simulation
September 29 - October 13, 2021: In this 3-part series, Simpleware customers and experts share their knowledge and experience in implementing AI workflows for patient-specific medical device development.
Improving Patient Outcomes with Patient-Specific Knee Models
Wednesday, September 29, 2021
This Simpleware webinar looks at researching implant designs using patient-specific knee models to investigate the effect of implants on joint mechanics. The work was carried out by Eindhoven University of Technology (TU/e), Maastricht University Medical Center, DSM, and Chemelot InSciTe.
Erkan Asik of TU/e presents how Simpleware software’s AI-based automated segmentation tools were used to rapidly generate models of the knee from MRI data, and how these are combined with CAD-designed devices for Finite Element Analysis. The approach discussed here shows the promise of applying image-based modeling and AI techniques to efficiently simulate implant design and improve patient outcomes by optimizing designs and reducing time-to-market.
In this webinar you will:
- See the steps taken to go from patient MRI scans to automated segmentation, meshing, and simulation
- Learn about recent AI-based techniques for working with patient image data
- Develop an understanding of current opportunities and challenges for patient-specific modeling and simulation workflows
Speakers:
Erkan Asik, PhD
Postdoctoral Researcher (Eindhoven University of Technology (TU/e)
Erkan is a post-doctoral researcher in the research group Orthopaedic Biomechanics of Eindhoven University of Technology (TU/e). Erkan is working on designing focal resurfacing implants for the knee joint in close collaboration with Maastricht University Medical Center, DSM, and Chemelot InSciTe. Erkan is specialized in damage and failure under mechanical loading and understanding relationship between microstructure and mechanical response. He holds a PhD in mechanical engineering, and BSc and MSc degrees in material science.
David Harman, PhD
Business Development Manager (草榴社区)
David is looking after the Simpleware software business in EMEA, South America and Asia, expanding these areas and spreading awareness of Simpleware software and service-based solutions for the generation of 3D image-based 3D printing and computational models. David completed his PhD in Composite Material Engineering at the University of Plymouth in 2013, examining robotic tufting for the through-thickness reinforcement of aerospace composites.
The Hip Detectives: Improving Clinical Outcomes by Leveraging Patient-Specific Orthopedic Surgical Planning
Thursday, October 7, 2021
In this presentation and panel discussion, 草榴社区 engineers, as well as researchers and surgeons from University College London (UCL) and the Royal National Orthopaedics Hospital (RNOH), talk about applications of 3D image-based patient-specific orthopedic surgical planning towards improving clinical/patient outcomes. This is a unique opportunity to learn from a very special group that crosses the spectrum of pure research to clinical applications, and we are very excited to have them present.
Topics Covered Include:
- The use of patient-specific orthopedic surgical planning for improving patient outcomes
- AI-enabled automatic segmentation of orthopedic CT images with Simpleware AS Ortho
- Challenges and solutions to segmentation for revision surgery
- 3D planning for 3D printing: from patient imaging to implant design
Panelists:
Anna Di Laura, PhD
Senior Research Associate (Royal National Orthopaedics Hospital (RNOH)
Anna is an orthopedic engineer with a background in biomedical engineering (BEng, MSc). She is the RNOH Implant Imaging Fellow and honorary Associate Professor at UCL. Her current research is aimed at a better understanding, through medical image computing, surgical planning and outcome assessment, how to improve hip function in patients with hip problems and hip replacements. She works daily with orthopedic surgeons, engineers and healthcare practitioners, and is responsible for the development and execution of software analysis for imaging studies of joint disease and reconstruction.
Johann Henckel
Researcher and Orthopaedic Surgeon (RNOH)
Johann is an orthopedic surgeon with research interests in developing imaging software solutions to aid the understanding of the biomechanics of the lower limb musculoskeletal system. His research includes surgical technology applied to hip and knee joint replacement with expertise in the field of robotics and computer assisted surgery.
Prpf Alister Hart
Orthopaedic Surgeon (University College London & RNOH)
Alister is the UCL chair of orthopedics and a consultant hip surgeon. He leads a research team of surgical technologists, based at the UCL Stanmore Campus & RNOH NHS Trust, focused on Implant Science and Surgical Imaging Technology, with Running for Science being a key project. Alister has pioneered the use of 3D printing for hip surgery, robotic surgery and the analysis of orthopedic implants. His research on implant science has led to changes to international health policy; development of clinical guidance in the UK and abroad; changes to clinical practice and subsequent cost savings.
Kerim Genc, PhD
Business Development Manager (草榴社区)
Kerim is the Business Development Manager for the Simpleware Product Group at 草榴社区. He joined Simpleware in 2011 as a Technical Sales Consultant and is currently responsible for managing global sales, business development and technical marketing content development. He received his BS and MS in biomechanics from the University of Calgary and the Pennsylvania State University respectively and completed his PhD in Biomedical Engineering at Case Western Reserve University looking at countermeasures to spaceflight induced bone loss and fracture risk.
Ross Cotton, PhD
Application Engineer Manager (草榴社区)
Ross joined the Simpleware product group in 2008 after receiving his PhD in Sports Engineering from Loughborough University (UK). The research combined experimental tests and numerical simulations to investigate the mechanics of a soccer ball impact. The results were used towards the development of the 2008 European Championships match ball. In his current position at 草榴社区, he oversees the AE team focused on technical support and training, and delivering service projects.
Making It REAL: In Silico Workflow from 4D CT to FEA
Wednesday, October 13, 2021
草榴社区, Duke University, Johns Hopkins University, and Thornton Tomasetti have teamed up to demonstrate a workflow for an in silico study of aortic valve frame deployments for 5 patients. The workflow includes:
- Automatic segmentation and landmarking (草榴社区) of 4D CT patient data (Duke) to define models for the aorta and left ventricle
- Utilizing the segmentations and landmarks to morph the models from time frame to time frame to model the cardiac motion (JHU)
- Conversion of the 4D models into the final FEA model (Thornton Tomasetti) to assess aortic valve frame deployment using Abaqus
The in silico approach can boost productivity and regulatory compliance for major manufacturers and agile startups alike. As the medical
devices industry moves towards a digital ecosystem, in silico trials are becoming a reality for the Medical Device industry. Join this webinar to discuss
how we can all cross the chasm between people's needs for digital solutions and their abilities to master the complexities of the required tools including
AI-based images segmentation and mechanistic, multi-physics simulation.
In this webinar you will learn about:
- AI-enabled automatic segmentation of the heart with Simpleware ScanIP and Simpleware AS Cardio
- Application of segmentation and landmarks to derive the cardiac motion through morphing
- Detailed FEA analysis on a heart valve frame deployment for 5 selected patient datasets
Speakers:
Elham Ramyar, PhD
Project Engineer (Thornton Tomasetti)
Elham is a PhD candidate in mechanics, materials and structure from Northwestern University about to graduate, and joined the Life Sciences team at Thornton Tomasetti in summer 2021. She is an expert in computational mechanics and model development. Her research focuses on computational model development for non-Newtonian fluid with direct applications in the modelling of rheological behavior of blood, DEM-CFD modelling of pharmaceutical process in drug delivery, and plaque build-up and stent thrombosis. She has been involved in FEA patient-specific heart and valve frame deployment modelling.
Can Ceritoglu, PhD
Assistant Research Associate (Johns Hopkins University)
Can Ceritoglu is Assistant Research Scientist in the Center for Imaging Science of The Johns Hopkins University. He earned his PhD in Electrical and Computer Engineering from Johns Hopkins University in 2008 and has been working in the fields of Medical Image Processing and Computational Anatomy with a particular focus on human brain registration and multi-atlas segmentation. Over the years, Can has worked on the development of quantitative medical image analysis tools that are run on the cloud-based medical image processing service BrainGPS and that are being used by various researchers in US.
Kerim Genc, PhD
Business Development Manager (草榴社区)
Kerim is the Business Development Manager for the Simpleware Product Group at 草榴社区. He joined Simpleware in 2011 as a Technical Sales Consultant and is currently responsible for managing global sales, business development and technical marketing content development. He received his BS and MS in biomechanics from the University of Calgary and the Pennsylvania State University respectively and completed his PhD in Biomedical Engineering at Case Western Reserve University looking at countermeasures to spaceflight induced bone loss and fracture risk.
Chris Goddard, PhD
Applications Engineer (草榴社区)
Chris has a PhD in computational Physics focusing on understanding chaotic/turbulent solutions that arise from numerical models for non-Newtonian fluids. He has had various roles in Design Engineering before joining 草榴社区 in 2018, where he assists with developing automatic image segmentation and processing tools for the Simpleware product.
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