Technology & Outreach – CompBioMed Conference

Education, Training & Public Awareness

Emily Lumley — Thu, 29 Nov 2018 16:54:30 +0000

Invited Speakers

Prof Benny Chain, University College London
Prof Rick Stevens, Argonne National Laboratory
Prof Andrea Townsend-Nicholson, University College London

Panelists

Dr Jeremy Yates, University College London
Dr Anneke Seller, Health Education England
Dr Nikolas Maniatis, University College London

Symposium Chair

Andrea Townsend-Nicholson, Professor of Biochemistry & Molecular Biology

Symposium Description

The ability to use computational methodologies to make explicit predictions of the behaviour of biomedical systems that are rapid, precise and accurate will make huge advances in personalised and precision medicine, ultimately leading to the ability to inform clinical decision-making on the timescale needed for patient care. To achieve this, future generations of scientists and medical practitioners need to be trained in the basic medical and clinical contexts of high-performance computing simulation.

Training of existing researchers in academia, industry and clinical practice, when complemented by education of medical, science and engineering students affords a means of providing the computational biomedicine expertise needed to realise this goal. In this symposium, we shall explore ways in which training and education strategies can be developed and delivered to a very heterogeneous set of end users at varying career stages, how these educational templates can be scaled and delivered to a large number of end users and how communities of practice for the next generation of computational biomedicine practitioners can be established.

Thursday 26th September, 13:00 – 15:00; Watson Watt Room

Time	Speaker	Title
13:00	Andrea Townsend-Nicholson (Invited Speaker)	Reflections on educating and engaging new communities of practice with high performance computing through the integration of teaching and research Abstract preview In my role as UCL lead for CompBioMed, a H2020 Centre of Excellence in Computational Biomedicine (compbiomed.eu), and as Head of Teaching for Molecular Biosciences at UCL, I have integrated research and teaching to lead the development of HPC-based education targeting medical students and undergraduate students studying biosciences in a way that has explicitly designed to be integrated into their existing university programmes as credit bearing courses. This innovation has not been replicated in any other university in the world. One version of the taught course has been designed for medical students in Years 1 and 2 of study (SSC334) and one of the unique features of the course is the integration of experimental and computational aspects, with students obtaining and processing biological samples, using state of the art Next Generation Sequencing and then interrogating the DNA sequences computationally using code that was ported to high performance computing (HPC) facilities of CompBioMed’s HPC Facility core partners (EPCC (UK), SURFsara (Netherlands) and the Barcelona Supercomputing Centre (Spain)). Another version of the taught course (BIOC0023) replaces the final year research project course for undergraduate biomedical science students, providing them with the opportunity to design and complete an entire research project from developing experimental hypotheses to investigating these in a way that involves the integration of experimental and computational methodologies. In the past 18 months, these UCL courses have successfully run with a total of ~250 students participating (60 medical students and 195 biomedical science students). Full Abstract
13:20	Benny Chain (Invited Speaker)	Computational biomedicine –interdisciplinary training for the clinician scientists of the future Abstract Preview The realisation that biological processes can be explained in terms of the interactions between a limited set of fundamental chemical building blocks has driven progress in biomedical science for more than a century, and has resulted in the molecular biology revolution. The key interdisciplinary boundary during this period was the frontier between medicine and chemistry. Today, however, a new set of challenges is changing the frontier of biomedicine. Technological advances in every area of biology have resulted in an exponential increase in the rate of data acquisition, and in its complexity. There is a growing consensus that the rate at which we are acquiring new hyper-dimensional biological data now outstrips our ability to analyse, integrate, interpret and eventually exploit it to drive progress in medicine and improve health. In order to tackle these challenges, biomedical scientists need new sets of skills. Specifically, mathematics offers a framework with the potential to simplify the increasingly complex data which is being produced, and provide fundamental rules which capture the behaviour of physiological systems in health and disease, and allow us to predict how they may respond to different types of therapeutic intervention. In parallel, artificial intelligence provides a means to implement this mathematics, using the increasingly sophisticated algorithms of machine learning. Full Abstract
13:40	Othmane Bouhali	Promoting a Research-Based Education through Undergraduate Research Experience for Students Abstract Preview Involving undergraduate students in research has proven to be an essential experience that enhances the learning outcome of students [1,2]. When exposed to research world at an early stage of their career, they acquire new skills that also guide them in tailoring their experience and choosing their future career. The High Energy and Medical Physics Group at Texas A&M University at Qatar (TAMUQ) has been supporting and engaging undergraduate students in different research projects in the areas of High Energy Physics and Medical Physics for the past six years. It attracted students from all four majors offered at TAMUQ, Electrical, Mechanical, Chemical and Petroleum Engineering shortly after the launching of its research activities. Many projects conducted within the group were awarded by the Qatar National Research Fund which is a governmental funding body that provides funding to highly competitive projects that address national priorities and contribute to capacity building [3]. Students were trained to use a high performance computing facility, different programming languages, software and Monte Carlo based platforms for their simulation. As for the outcomes, they participated and presented at international conferences, many of them attended CERN summer internship program. Some of the published journals in international peer-reviewed scientific journals. In this paper, we present some of the projects that our students completed, the different tools that were used, as well as the research outcomes. Then, we will discuss the impact of this experience on their learning and undergraduate education as well as their career path, especially their postgraduate studies. Full Abstract
13:55	Rick Stevens (Invited Speaker)	AI for Science Abstract Preview In this talk, I will describe an emerging initiative at Argonne National Laboratory to advance the concept of Artificial Intelligence (AI) aimed at addressing challenge problems in science. We call this initiative “AI for Science”. The basic concept is threefold: (1) to identify those scientific problems where existing AI and machine learning methods can have an immediate impact (and organize teams and efforts to realize that impact); (2) identify areas of where new AI methods are needed to meet the unique needs of science research (frame the problems, develop test cases, and outline work needed to make progress); and (3) to develop the means to automate scientific experiments, observations, and data generation to accelerate the overall scientific enterprise. Science offers plenty of hard problems to motivate and drive AI research, from complex multimodal data analysis, to integration of symbolic and data intensive methods, to coupling large-scale simulation and machine learning to drive improved training to control and accelerate simulations. A major sub-theme is the idea of working toward the automation of scientific discovery through integration of machine learning (active learning and reinforcement learning) with simulation and automated high-throughput experimental laboratories. I will provide some examples of projects underway and lay out a set of long-term driver problems. Full Abstract
14:15	Mariana Pereira da Costa	Integrating Computational Biology and Soil Metagenomics: an Undergraduate study
14:30	Panel Discussion
15:00	REFRESHMENTS

Innovation in Modern Biotechnology

Emily Lumley — Thu, 29 Nov 2018 16:53:50 +0000

Invited Speakers

Mariano Vazquez, Barcelona Supercomputing Centre
Cristin Merritt, Alces-Flight
Luca Emili, InSilicoTrials
Raimondas Galvelis, Acellera

Symposium Chair

Herman Van Vlijmen, Head of Molecular Sciences

Symposium Description

This symposium covers examples of development of academic research in biomedical computational simulations into commercial opportunities. Presentation topics can include (but are not limited to) commercialisation of software, companies that use computation as an essential component in product design and/or development, or setting up expert consultancy services. Success stories, pitfalls, and practical considerations are all of great value to share with the community of biomedical computational simulations.

Thursday 26th September, 13:00 – 15:00; Turing Lecture Theatre

Time	Speaker	Title
13:00	Mariano Vazquez (Invited Speaker)	ELEM Biotech – The Virtual Humans Factory Abstract Preview In Barcelona, July 2018, the Barcelona Supercomputing Center (BSC), the Technical University of Catalonia (UPC), the Spanish Superior Council of Scientific Research (CSIC), three researchers and a business-background entrepreneur, founded the start-up company ELEM Biotech (http://www.elem.bio). The company is in charge of developing and commercialize a set of high-tech simulation technology targeting the biomedical sector. The core technology is Alya, the parallel multi-scale / multi-physics simulation software developed at the Barcelona Supercomputing Center, by a team led by Mariano Vázquez and Guillaume Houzeaux. The company is based in Barcelona, with an office in Bristol (UK). Full Abstract
13:20	Cristin Merritt (Invited Speaker)	Balancing Research and Production: Alces Flight’s take on building up commercial compute Abstract Preview There are typically two complementary types of compute workload taking place in academic groups looking to spin-off into commercial entities: 1. Your known, production workflows which are showing promise for building up a company that can pioneer the way forward in science. 2. Your unknown, research concepts, ideas, and emerging workflows that can feed the cycle of improvement. So how do you build up commercial compute without expending too much time and killing your budget in betting on the wrong resources? For the past three years Alces Flight has been studying how public cloud is impacting High Performance Computing (HPC) as an emerging platform. Our exploration moved us to initially create a tool designed to launch an HPC environment straight in the cloud – but what we learned along the way has made us re-evaluate how emerging business can harness different resources in order to build a smart cycle of compute that can feed academics transitioning into company life. At the September, 2019 CompBioMed Conference we wish to share the insights made in: • Honing characteristics of your workload to understand what constitutes production (paid commercial) work and what constitutes the research to feed improvements. • Understanding how spreading your compute budget can help you not only survive getting started, but make strong future investments. • Balancing both free and paid technologies and services to avoid the trap of believing you can do everything in-house. Full Abstract
13:40	Raimondas Galvelis (Invited Speaker)	The rise of PlayMolecule Abstract Preview Since the earliest virtual models of molecules and simulations, incredible efforts in technology and methodology have brought forth solutions and tools now employed in the understanding of biomolecular interactions and prediction of their properties. The development and performance of these solutions were challenged by their diversity but have definitely lead to the increased use of computerized methods in a wide range of research fields, from genomics to drug design. Acellera has acquired a strong expertise in software development and structural studies over the last 10 years. We designed, alone or in collaboration, innovative solutions for the understanding of critical events for molecular recognition like ligand binding and conformational changes of biomolecules, key steps in the drug design process. Complex protocols combined with the need for high performance infrastructure hampered the access and use of such solutions by the whole scientific community dedicated to Drug Discovery. Full Abstract
14:00	Luca Emili (Invited Speakers)	InSilicoTrials.Com: A Cloud-Based Platform to Drive Technology Transfer of Modeling and Simulation Tools across Healthcare Abstract Preview For decades, universities and research centers have been applying modeling and simulation (M&S) to medical devices [1] and pharmaceutical [2] development, coining the new expression in silico clinical trials. Its use however is still limited to a restricted pool of specialists. Making M&S available to a broad spectrum of potential users (medical device and pharmaceutical companies, hospitals, healthcare institutions) would require an easy and controlled access to M&S resources in a secure environment. A joint effort between academia, industry and regulatory bodies is therefore needed to reach a rapid adoption of a harmonized approach. It is here proposed an easy-to-use cloud-based platform that aims to create a collaborative marketplace for M&S in healthcare, where developers and models’ creators are able to capitalize on their work while protecting their intellectual property (IP), and medical device and pharmaceutical companies can use M&S to accelerate time and to reduce costs of their research and development (R&D) processes. Full Abstract
14:20	Panel Discussion
15:00	REFRESHMENTS

Cloud & High Performance Computing

Emily Lumley — Thu, 29 Nov 2018 16:53:30 +0000

Invited Speakers

Dr Alexandre Bonvin, Utrecht University
Dr Andrew Grant, Atos
Dr Wolfgang Gentzsch, UberCloud

Symposium Chair

Marco Verdicchio, IT Consultant, SURFsara

Symposium Description

High fidelity biomedical simulation addresses systems of immense complexity, in three dimensional space as well as time. This frequently calls for access to very powerful computers, including the most powerful ones available globally today. For applications in clinical medicine, modelling and simulation based on personal data must be conducted not only with high fidelity, and in a secure manner to address information governance regulations, but also rapidly since the outcomes should be actionable, in the sense of providing real time decision support for clinicians.

Topic for consideration include, but are not limited to, high performance computing (HPC) requirements for biomedical applications, such as software development, scalability of codes and other associated performance metrics, as well as support for access mechanisms which are unconventional by traditional HPC centre standards (such as advance reservation and urgent computing), the use of visualisation and computational steering along with secure data staging and storage. Modern commercial cloud environments can be brought increasingly seamlessly into juxtaposition with HPC resources, and the two technologies further aligned through new technologies such as containerisation. Cybersecurity and quality of service are key metrics for assessing the reliability and performance of these technologies.

Thursday 26th September, 15:30 – 17:00; Watson Watt Room
and
Friday 27th September, 10:15 – 12:00; Watson Watt Room

Time	Speaker	Title
15:30	Wolfgang Gentzsch (Invited Speaker)	Advancing Personalized Healthcare with High-Performance Cloud Computing for the Living Heart Project Abstract preview Major factors contributing to the acceleration of personalized healthcare in recent years come from advances in high-performance computing (HPC), data analytics, machine learning, and artificial intelligence, enabling scientists now to perform the most sophisticated simulations, in genomics, proteomics, and many other fields, using methods like genome analysis, molecular dynamics, and more general computer aided analysis methods widely applied and proven in other areas of scientific and engineering modelling. To just select one, we demonstrate the impact of computer simulations on personalized health care and present a research project aiming at living heart simulations, which has recently been rewarded with several prestigious international awards. Full Abstract
15:50	Stefan Zasada	Large Scale Binding Affinity Calculations on Commodity Compute Clouds Abstract Preview In recent years it has become possible to calculate the binding affinities of compounds bound to proteins via rapid, accurate, precise and reproducible free energy calculations. The ability to do so has applications from drug discovery to personalised medicine. This approach is based on molecular dynamics simulations and draws on sequence and structural information of the protein and compound concerned. Free energies are determined by ensemble averages of many molecular dynamics replicas, each of which requires hundreds of CPU or GPU cores, typically requiring a supercomputer class resources to be calculated on a tractable timescale. In order to perform such calculations there are also requirements for initial model building and subsequent data analysis stages. Full Abstract
16:05	Piotr Nowakowski	Processing Complex Medical Workflows in the EurValve Environment Abstract Preview In this paper we present the outcome of three years of development work in the EurValve project [1] which resulted in the creation of an integrated solution for medical simulations referred to as the Model Execution Environment (MEE). Starting with a definition of the problem (which involves simulating valvular heart conditions and the outcomes of treatment procedures) we provide a description of the high-performance computational environment utilized to process retrospective use cases in order to create a knowledge base which underpins the EurValve Decision Support System (DSS). We also provide specific examples of MEE usage and the corresponding statistics. Full Abstract
16:20	Terry Sloan	The HemeLB Offloader Abstract Preview is paper outlines an approach for enabling access to HPC applications as Software as a Service (SaaS) on conventional high-end HPC hosts such as EPCC’s Cirrus and cloud providers such as Microsoft’s Azure service. The focus for the approach is enabling access to the HemeLB application with the Polnet biomedical workflow. The paper reports on an implementation of this approach that allows Polnet workflows to run on the Cirrus and LISA supercomputing services at EPCC and SURFsara respectively. Full Abstract
16:35	Alexandre Bonvin (Invited Speaker)	Structural biology in the clouds: Past, present and future Abstract Preview Structural biology deals with the characterization of the structural (atomic coordinates) and dynamic (fluctuation of atomic coordinates over time) properties of biological macromolecules and adducts thereof. Gaining insight into 3D structures of biomolecules is highly relevant with numerous application in health and food sciences. Since 2010, the WeNMR project (www.wenmr.eu) has implemented numerous web-based services to facilitate the use of advanced computational tools by researchers in the field, using the grid computational infrastructure provided by EGI. These services have been further developed in subsequent initiatives under the H2020 EGI-ENGAGE West-Life project and the BioExcel Center of Excellence for Biomolecular Computational Research (www.bioexcel.eu). The WeNMR services are currently operating under the European Open Science Cloud with the H2020 EOSC-Hub project (www.eosc-portal.eu), with the HADDOCK portal (haddock.science.uu.nl) sending >10 millions jobs and using ~2700 CPU years per year. In my talk, I will summarize 10 years of successful use of e-infrastructure solutions to serve a large worldwide community of users (>13’500 to date), providing them with user-friendly, web-based solutions that allow to run complex workflows in structural biology. Full Abstract
16:55	END OF SESSION AND DAY 2

Time	Speaker	Title
10:15	Tomasz Piontek	Supporting advanced HPC/HTC scientific workloads with QCG services Abstract preview All researchers agree that efficiency, flexibility and ease of execution of scientific computation workloads were always key requirements of in-silico experiments. Nowadays, when the computational facilities reach exascale and the complexity of applications increases, the situation hasn’t changed. There are still the same questions and unresolved practical problems how to perform computations easily and effectively. Full Abstract
10:30	Christos Kotsalos	Digital Blood in Massively Parallel CPU/GPU Systems for the Study of Platelets deposition Abstract Preview We propose a novel high-performance computational framework for the simulation of fully resolved whole blood flow. The framework models blood constituents like red blood cells (RBCs) and platelets individually, including their detailed non-linear elastic properties and the complex interactions among them. This kind of simulations are particularly challenging because the large number of blood cells (up to billions) stand in contrast with the high computational requirement of individual constituents. While classical approaches address this challenge through simplified structural modelling of the deformable bodies (e.g., through mass-spring systems), the present framework guarantees accurate physics, desirable numerical properties through a fully featured FEM model and computational efficiency at the same order as the more simplified state-of-the-art models. The required numerical performance is achieved through a hybrid implementation, using CPUs for the blood plasma and GPUs for the blood cells. Full Abstract
10:45	Craig Lucas	The POP Centre of Excellence – Improving Parallel Codes Abstract Preview The Performance Optimisation and Productivity (POP) Centre of Excellence [1] is funded through Horizon 2020, like CompBioMed, and is made up of eight partners across Europe [2]. Our remit is to improve the performance of both academic and commercial parallel codes. Working with developers and users we promote a methodology for understanding a code’s performance which helps us go on to improve it. Full Abstract
11:00	Narges Zarrabi	Secure Processing of Sensitive Data on shared HPC systems Abstract Preview In this work we present a novel method for creating secure computing environments on traditional multi-tenant high-performance computing clusters. Typically, current HPC clusters operate in a shared and batch mode, which can be incompatible with the security requirements set by data providers for processing their highly sensitive data. We propose a solution using hardware and network virtualization, which runs on an existing HPC cluster, and at the same time, meets strict security requirements. We show how this setup was used in two real-world cases. The solution can be used generally for processing sensitive data. Full Abstract
11:15	Shantenu Jha	Zettascale Computing on an Exascale Platform Abstract Preview We outline the vision of “Learning Everywhere” which captures the possibility and impact of learning methods coupled to traditional HPC methods. A primary driver of such coupling is the promise that learning will give major effective performance improvements for traditional HPC simulations. We will discuss how learning methods and HPC simulations are being integrated, and provide representative examples. We will discuss specific applications and software systems developed for ML driven MD simulations on Summit at Oak Ridge. Full Abstract
11:30	Phil Tooley	Parallelising Image Registration and the HPC Porting Journey Abstract Preview Image registration is widely used in many areas of computational biomedicine, both as a research tool and a component in work flows providing clinical decision support. There exists a wide range of both open-source and commercial tools for performing image registration based on a variety of dierent methods.[1] However, these tools are designed to be run on a single machine, with the associated limitations of computational performance and available memory of the system, placing a limit on the maximum size of images which can be handled. A key application for image registration at the University of Sheeld is strain measurement of bone samples using digital volume correlation (DVC).[2] This makes use of tomographic imaging from synchrotron light sources, which can be many tens to hundreds of gigabytes in size \| too large to be handled at full resolution by these existing codes. The solution is therefore to create a parallelised image registration code, capable of leveraging HPC infrastructure to register images of such sizes using the memory and computational capacity of multiple HPC nodes. Full Abstract
11:45	Andy Grant (Invited Speaker)	Integrating HPC and Deep Learning in converged workflows Abstract Preview In the last few years the use of AI and specifically deep learning techniques has emerged as a key pillar in scientific discovery. While many of the underlying techniques have been around for some time the computational power and data volumes required to make them effective have only recently become available. Deep Learning provides new methods to improve predictive accuracy, response times and insight into new phenomena, often using data sets that would previously have been considered unmanageable. Full Abstract
12:05	LUNCH

Regulatory Science and in silico Trials

Emily Lumley — Thu, 29 Nov 2018 16:51:43 +0000

Invited Speakers

Dr Tina Morrison, US Food and Drug Administration, USA (TBC)
Dr Flora Musuamba, European Medicines Agency

Symposium Co-Chairs

Alfons Hoekstra, Assistant Professor, University of Amsterdam
Marco Viceconti, Professor of Computational Biomechanics, University of Bologna

Symposium Description

An important application of Virtual Human technology are In-Silico Trials (IST). ISTs should contribute to the three R’s, refinement, reduction, or replacement of pre-clinical and clinical trials. Driven forward by the Virtual Human community, the Food and Drug Administration (FDA) in the US, the European Medical Association (EMA), and the Avicenna Alliance, and with funding through, for example, the European Commission, a number of projects developing and applying ISTs are underway. The challenges they face are multifaceted, ranging from validating the underlying in-silico models of specific pathophysiology or applied virtual populations, via technological and infrastructural demands, to regulatory issues. The goal of this special symposium is to bring together key stake holders in the current development of ISTs, to highlight state-of-the-art developments, to discuss the challenges that ISTs are facing, and to contribute to next steps in successfully applying IST in actual (pre-)clinical settings.

Thursday 26th September, 10:15 – 12:00; Watson Watt Room

Time	Speaker	Title
10:15	Flora Musuamba Tshinanu (Invited Speaker)	In silico trials and drug approval process: where are we? Abstract preview Marketing approvals of (new) medicinal products (and combinations) generates large interests of both patients in need of new medicinal therapies and the sponsors (big pharmaceutical industry, SMEs, and academia). Before a new medical product can be used on humans in a country, it must be approved for that use by the relative Regulatory Authority of that country. In USA, this will be the remit of the Food and Drug Administration (FDA) drugs and medical devices whereas in the European Union pharmaceuticals are approved by the European Medicine Agency (EMA) mostly and by national competent authorities to a lesser extent. The approval of medical devices is delegated to the member states, through selected notified bodies. Consequently, regulators have to find the appropriate balance between the need to ensure that decision-making is based on scientifically valid data and the need for access to the new medicines is considered. Full Abstract
10:35	Georgia Karanasiou	InSilc: an in silico clinical trials platform for advancing BVS design and development Abstract Preview Coronary Artery Disease (CAD) is the leading cause of death in Europe and worldwide with more than 17 million deaths [1]. Atherosclerosis, the major disease process of CAD, is a chronic inflammation driven by the build-up of atherosclerotic plaques inside the coronary arteries. Bioresorbable Vascular Scaffolds (BVS) revolutionised the field of interventional cardiology by providing targeted drug delivery, mechanical support and complete resorption overcoming the barriers of bare-metal and drug-eluting stents. In vitro and in vivo experiments followed by clinical trials are currently used in providing useful information on the safety and efficacy of BVS. However, these processes are time-consuming and costly. In parallel, they raise ethical considerations due to the uncertainty related to the extremely well performance in controlled laboratory experiments and pre-clinical studies, and potential under performance during or after clinical trials. Full Abstract
10:50	Francesco Pappalardo	Credibility of UISS-TB modelling and simulation framework Abstract Preview In-Silico Trials (IST) represent an innovative application of Virtual Human technology helpful in assisting and supporting the refinement, the reduction, or the replacement of pre-clinical and clinical trials. In this multifaceted challenge perspective, the regulatory authorities are facing with an increasing number of projects developing and applying ISTs ranging from validating underway in-silico models of specific pathophysiology or applied virtual populations, via technological and infrastructural demands. The last few years have been characterised by an intense activity around the so-called regulatory science, aimed to ensure a robust approach to assess the credibility of individual in-silico methods as sources of regulatory evidence (Viceconti et al., 2017; Pappalardo et al., 2018a; Morrison et al., 2018). Full Abstract
11:05	Marco Viceconti	Modelling bone at the tissue scale: the missing link between drug design and clinical outcome Abstract Preview The clinical assessment of new drugs against osteoporosis is a particularly expensive one. Ideally a clinical trial should have fragility fractures as primary outcome, and should follow-up patients for at least five years, but this would bring the cost and time-to-market to unacceptable levels. A quick search on https://clinicaltrials.gov shows that Romosozumab, one of the latest drugs brought to market has been studies either with indirect outcome metrics (such as bone density), or at most observing fractures over 24 months. While this is probably adequate for the specific purposes of those trials, the possibility to assess the efficacy of these new drugs with in silico trials is of extreme interest. Full Abstract
11:20	Nenad Filipovic	In Silico trials for drug tracing the effects of sarcomeric protein mutations leading to familial cardiomyopathy- SILICOFCM project Abstract Preview Familial cardiomyopathies (FCM) are most commonly diagnosed, or progress of the disease is monitored, through in vivo imaging, with either echocardiography or, increasingly, cardiac magnetic resonance imaging (MRI). The treatment of symptoms of FCM by established therapies could only in part improve the outcome, but novel therapies need to be developed to affect the disease process and time course more fundamentally. In SILICOFCM project we are doing in silico multiscale modeling of FCMs that would take into consideration comprehensive list of patient specific features (genetic, biological, pharmacologic, clinical, imaging and patient specific cellular aspects) capable of optimizing and testing medical treatment strategy with the purpose of maximizing positive therapeutic outcome, avoiding adverse effects, avoiding drug interactions, preventing sudden cardiac death, shortening time between the drug treatment commencement and the desired result. Full Abstract
11:35	Tina Morrison (Invited Speaker)	TBC
12:00	LUNCH

Imaging & Visualisation

Emily Lumley — Thu, 29 Nov 2018 16:50:46 +0000

Invited Speakers

Prof Abbes Amira, Qatar University
Guillermo Marin, Barcelona Supercomputing Center
Dr Thomas Odaker, LRZ

Symposium Chair

Fernando Cucchietti, Data Pre and Post Processing Group Manager
Peter Coveney, UCL

Symposium Description

Imaging & Visualisation remain a cornerstone of modern medicine, allowing us to represent all the data that comes out of medical test devices as well as computer simulations. Furthermore, they are also key for medical science communication and education. In the era of virtual humans, imaging and visualisation will become ever more complex, as we get access to more and different data from simulations.

In this Symposium we will explore new imaging & visualisation techniques, applications, and technology as we discuss the new requirements of this nascent field.

Friday 27th September, 13:00 – 15:00; Watson Watt Room

Time	Speaker	Title
13:00	Abbes Amira (Invited Speaker)	Accelerating Medical Imaging on Multi-core Platforms Abstract preview In this invited talk, we will address different software and hardware issues related to the design and implementation of medical imaging systems using reconfigurable computing and multicore platforms. A range of algorithms, including discrete wavelet transform (DWT), Ridgelet and Curvelet transforms will be presented for imaging applications such as medical image denoising, segmentation and compression. The implementation process of these algorithms on reconfigurable platforms will be described. In addition, we will review the latest reconfigurable hardware technologies and development methods for real-time embedded and high performance computing systems, and will conclude with comprehensive case studies demonstrating the deployment of low power reconfigurable architectures for algorithms acceleration and performance evaluation methods for reconfigurable medical imaging systems. Full Abstract
13:20	Thomas Odaker (Invited Speaker)	Improved Data Analysis with Virtual and Augmented Reality Abstract Preview The Leibniz Supercomputing Centre (LRZ) of the Bavarian Academy of Sciences and Humanities is not only IT service provider for the Munich Universities but competent and reliable research partner as well. Over the last decade, the LRZ has acquired great expertise in the field of visualisation while focusing primarily on the topics of Virtual Reality (VR) and – more recently – Augmented Reality (AR). Large-scale VR installations (such as CAVE-like systems [1] or ultra-high resolution stereoscopic displays) have been a staple in certain industries for decades. Their complexity and cost, though, have always been a limiting factor and prevented the widespread availability and use. However, thanks to advances in hardware and software development over the last few years, VR technologies have taken a leap forward in terms of accessibility, usability, quality, and affordability, especially with regards to head mounted displays (HMDs). Full Abstract
13:40	Abbes Amira	Automatic Cerebral Aneurysm Segmentation Using Contourlet Transform and Hidden Random Field Model Template Abstract Preview Cerebral Aneurysm (CA) is a vascular disease that affects almost 1.5 – 5% of the general population, mostly adults. Sub-Arachnoid Hemorrhage, caused by a ruptured CA, has high morbidity and mortality rates. Therefore, radiologists aim to detect and diagnose this disease at an early stage to prevent or reduce its consequential damages. This work contributes to the CA segmentation field by proposing a novel automated algorithm. Precisely, the contourlet transform, as a multiresolution technique, and Hidden Markov Random Field with Expectation Maximization, as a statistical technique, are the two main adopted approaches. The first technique helps in extracting images features not apparent in the normal image scale; while the second technique segments images in the contourlet domain based on the spatial contextual constraints. The proposed algorithm reveals promising results on the tested Three-Dimensional Rotational Angiography (3D RA) datasets, where both an objective and a subjective evaluation are carried out. Full Abstract
13:55	Guillermo Marin (Invited Speaker)	Animating the Virtual Human: Applying movie-industry tools and techniques to data visualization Abstract Preview Impactful and memorable images are a great resource for science dissemination, improving the reach and engagement of complex and information rich topics. Yet scientists in general do not have the training nor the time to create high quality and appealing imagery, and journalists and designers do not have a deep understanding of the data itself nor the tools to deal with scientific datasets. On its own, each group can more easily fall into the traps of either detailed but uninteresting imagery, or non-rigorous “artist’s rendition” style of visuals generally dismissed by the domain scientists. However, when both scientists and designers work together, they can create accurate and appealing images and stories. Furthermore, from the interaction new approaches appear, like the one we present here. Inspired by popular web libraries that have allowed journalists and designers to incorporate data in their workflow and produce high quality visualizations, we created a pipeline and a set of tools that allow designers and animators to import large scientific datasets (from 3D simulations) directly into industry level software tools (Maya, Blender, Adobe suite, etc.) where they can control and manipulate the visual style more precisely, and reach higher levels of visual quality than with scientific visualization tools. On the other hand, the scientists can become more than simple advisors to the designers, and (thanks to the automation afforded by the coupled tools) create new visualizations for their publications and presentations. Full Abstract
14:15	Panel Discussion
15:00	REFRESHMENTS