Illustrative Flow Visualization of 4D PC-MRI Blood Flow and CFD Data

Das zentrale Thema dieser Dissertation ist die Anwendung illustrativer Methoden auf zwei bisher ungelöste Probleme der Strömungsvisualisierung. Das Ziel der Strömungsvisualisierung ist die Bereitstellung von Software, die Experten beim Auswerten ihrer Strömungsdaten und damit beim Erkenntnisgewinn unterstützt. Bei der illustrativen Visualisierung handelt es sich um einen Zweig der Visualisierung, der sich an der künstlerischen Arbeit von Illustratoren orientiert. Letztere sind darauf spezialisiert komplizierte Zusammenhänge verständlich und ansprechend zu vermitteln. Die angewendeten Techniken werden in der illustrativen Visualisierung auf reale Daten übertragen, um die Effektivität der Darstellung zu erhöhen. Das erste Problem, das im Rahmen dieser Dissertation bearbeitet wurde, ist die eingeschränkte Verständlichkeit von komplexen Stromflächen. Selbstverdeckungen oder Aufrollungen behindern die Form- und Strömungswahrnehmung und machen diese Flächen gerade in interessanten Strömungssituationen wenig nützlich. Auf Basis von handgezeichneten Strömungsdarstellungen haben wir ein Flächenrendering entwickelt, das Silhouetten, nicht-photorealistische Beleuchtung und illustrative Stromlinien verwendet. Interaktive Flächenschnitte erlauben die Exploration der Flächen und der Strömungen, die sie repräsentieren. Angewendet auf verschiedene Stromflächen ließ sich zeigen, dass die Methoden die Verständlichkeit erhöhen, v.a. in Bereichen komplexer Strömung mit Aufwicklungen oder Singularitäten. Das zweite Problem ist die Strömungsanalyse des Blutes aus 4D PC-MRI-Daten. An diese relativ neue Datenmodalität werden hohe Erwartungen für die Erforschung und Behandlung kardiovaskulärer Krankheiten geknüpft, da sie erstmals ein dreidimensionales, zeitlich aufgelöstes Abbild der Hämodynamik liefert. Bisher werden 4D PC-MRI-Daten meist mit Werkzeugen der klassischen Strömungsvisualisierung verarbeitet. Diese werden den besonderen Ansprüchen der medizinischen Anwender jedoch nicht gerecht, die in kurzer Zeit eine übersichtliche Darstellung der relevanten Strömungsaspekte erhalten möchten. Wir haben ein Werkzeug zur visuellen Analyse der Blutströmung entwickelt, welches eine einfache Detektion von markanten Strömungsmustern erlaubt, wie z.B. Jets, Wirbel oder Bereiche mit hoher Blutverweildauer. Die Grundidee ist hierbei aus vorberechneten Integrallinien mit Hilfe speziell definierter Linienprädikate die relevanten, d.h. am gefragten Strömungsmuster, beteiligten Linien ausgewählt werden. Um eine intuitive Darstellung der Resultate zu erreichen, haben wir uns von Blutflußillustrationen inspirieren lassen und präsentieren eine abstrakte Linienbündel- und Wirbeldarstellung. Die Linienprädikatmethode sowie die abstrakte Darstellung der Strömungsmuster wurden an 4D PC-MRI-Daten von gesunden und pathologischen Aorten- und Herzdaten erfolgreich getestet. Auch die Evaluierung durch Experten zeigt die Nützlichkeit der Methode und ihr Potential für den Einsatz in der Forschung und der Klinik.This thesis’ central theme is the use of illustrative methods to solve flow visualization problems. The goal of flow visualization is to provide users with software tools supporting them analyzing and extracting knowledge from their fluid dynamics data. This fluid dynamics data is produced in large amounts by simulations or measurements to answer diverse questions in application fields like engineering or medicine. This thesis deals with two unsolved problems in flow visualization and tackles them with methods of illustrative visualization. The latter is a subbranch of visualization whose methods are inspired by the art work of professional illustrators. They are specialized in the comprehensible and esthetic representation of complex knowledge. With illustrative visualization, their techniques are applied to real data to enhance their representation. The first problem dealt with in this thesis is the limited shape and flow perception of complex stream surfaces. Self-occlusion and wrap-ups hinder their effective use in the most interesting flow situations. On the basis of hand-drawn flow illustrations, a surface rendering method was designed that uses silhouettes, non-photorealistic shading, and illustrative surface stream lines. Additionally, geometrical and flow-based surface cuts allow the user an interactive exploration of the surface and the flow it represents. By applying this illustrative technique to various stream surfaces and collecting expert feedback, we could show that the comprehensibility of the stream surfaces was enhanced – especially in complex areas with surface wrap-ups and singularities. The second problem tackled in this thesis is the analysis of blood flow from 4D PC-MRI data. From this rather young data modality, medical experts expect many advances in the research of cardiovascular diseases because it delivers a three-dimensional and time-resolved image of the hemodynamics. However, 4D PC-MRI data are mainly processed with standard flow visualizaton tools, which do not fulfill the requirements of medical users. They need a quick and easy-to-understand display of the relevant blood flow aspects. We developed a tool for the visual analysis of blood flow that allows a fast detection of distinctive flow patterns, such as high-velocity jets, vortices, or areas with high residence times. The basic idea is to precalculate integral lines and use specifically designed line predicates to select and display only lines involved in the pattern of interest. Traditional blood flow illustrations inspired us to an abstract and comprehensible depiction of the resulting line bundles and vortices. The line predicate method and the illustrative flow pattern representation were successfully tested with 4D PC-MRI data of healthy and pathological aortae and hearts. Also, the feedback of several medical experts confirmed the usefulness of our methods and their capabilities for a future application in the clinical research and routine

Doctor of Philosophy

dissertationVisualization and exploration of volumetric datasets has been an active area of research for over two decades. During this period, volumetric datasets used by domain users have evolved from univariate to multivariate. The volume datasets are typically explored and classified via transfer function design and visualized using direct volume rendering. To improve classification results and to enable the exploration of multivariate volume datasets, multivariate transfer functions emerge. In this dissertation, we describe our research on multivariate transfer function design. To improve the classification of univariate volumes, various one-dimensional (1D) or two-dimensional (2D) transfer function spaces have been proposed; however, these methods work on only some datasets. We propose a novel transfer function method that provides better classifications by combining different transfer function spaces. Methods have been proposed for exploring multivariate simulations; however, these approaches are not suitable for complex real-world datasets and may be unintuitive for domain users. To this end, we propose a method based on user-selected samples in the spatial domain to make complex multivariate volume data visualization more accessible for domain users. However, this method still requires users to fine-tune transfer functions in parameter space transfer function widgets, which may not be familiar to them. We therefore propose GuideME, a novel slice-guided semiautomatic multivariate volume exploration approach. GuideME provides the user, an easy-to-use, slice-based user interface that suggests the feature boundaries and allows the user to select features via click and drag, and then an optimal transfer function is automatically generated by optimizing a response function. Throughout the exploration process, the user does not need to interact with the parameter views at all. Finally, real-world multivariate volume datasets are also usually of large size, which is larger than the GPU memory and even the main memory of standard work stations. We propose a ray-guided out-of-core, interactive volume rendering and efficient query method to support large and complex multivariate volumes on standard work stations

From Molecules to the Masses : Visual Exploration, Analysis, and Communication of Human Physiology

Det overordnede målet med denne avhandlingen er tverrfaglig anvendelse av medisinske illustrasjons- og visualiseringsteknikker for å utforske, analysere og formidle aspekter ved fysiologi til publikum med ulik faglig nivå og bakgrunn. Fysiologi beskriver de biologiske prosessene som skjer i levende vesener over tid. Vitenskapen om fysiologi er kompleks, men samtidig kritisk for vår forståelse av hvordan levende organismer fungerer. Fysiologi dekker en stor bredde romlig-temporale skalaer og fordrer behovet for å kombinere og bygge bro mellom basalfagene (biologi, fysikk og kjemi) og medisin. De senere årene har det vært en eksplosjon av nye, avanserte eksperimentelle metoder for å detektere og karakterisere fysiologiske data. Volumet og kompleksiteten til fysiologiske data krever effektive strategier for visualisering for å komplementere dagens standard analyser. Hvilke tilnærminger som benyttes i visualiseringen må nøye balanseres og tilpasses formålet med bruken av dataene, enten dette er for å utforske dataene, analysere disse eller kommunisere og presentere dem. Arbeidet i denne avhandlingen bidrar med ny kunnskap innen teori, empiri, anvendelse og reproduserbarhet av visualiseringsmetoder innen fysiologi. Først i avhandlingen er en rapport som oppsummerer og utforsker dagens kunnskap om muligheter og utfordringer for visualisering innen fysiologi. Motivasjonen for arbeidet er behovet forskere innen visualiseringsfeltet, og forskere i ulike anvendelsesområder, har for en sammensatt oversikt over flerskala visualiseringsoppgaver og teknikker. Ved å bruke søk over et stort spekter av metodiske tilnærminger, er dette den første rapporten i sitt slag som kartlegger visualiseringsmulighetene innen fysiologi. I rapporten er faglitteraturen oppsummert slik at det skal være enkelt å gjøre oppslag innen ulike tema i rom-og-tid-skalaen, samtidig som litteraturen er delt inn i de tre høynivå visualiseringsoppgavene data utforsking, analyse og kommunikasjon. Dette danner et enkelt grunnlag for å navigere i litteraturen i feltet og slik danner rapporten et godt grunnlag for diskusjon og forskningsmuligheter innen feltet visualisering og fysiologi. Basert på arbeidet med rapporten var det særlig to områder som det er ønskelig for oss å fortsette å utforske: (1) utforskende analyse av mangefasetterte fysiologidata for ekspertbrukere, og (2) kommunikasjon av data til både eksperter og ikke-eksperter. Arbeidet vårt av mangefasetterte fysiologidata er oppsummert i to studier i avhandlingen. Hver studie omhandler prosesser som foregår på forskjellige romlig-temporale skalaer og inneholder konkrete eksempler på anvendelse av metodene vurdert av eksperter i feltet. I den første av de to studiene undersøkes konsentrasjonen av molekylære substanser (metabolitter) ut fra data innsamlet med magnetisk resonansspektroskopi (MRS), en avansert biokjemisk teknikk som brukes til å identifisere metabolske forbindelser i levende vev. Selv om MRS kan ha svært høy sensitivitet og spesifisitet i medisinske anvendelser, er analyseresultatene fra denne modaliteten abstrakte og vanskelige å forstå også for medisinskfaglige eksperter i feltet. Vår designstudie som undersøkte oppgavene og kravene til ekspertutforskende analyse av disse dataene førte til utviklingen av SpectraMosaic. Dette er en ny applikasjon som gjør det mulig for domeneeksperter å analysere konsentrasjonen av metabolitter normalisert for en hel kohort, eller etter prøveregion, individ, opptaksdato, eller status på hjernens aktivitetsnivå ved undersøkelsestidspunktet. I den andre studien foreslås en metode for å utføre utforskende analyser av flerdimensjonale fysiologiske data i motsatt ende av den romlig-temporale skalaen, nemlig på populasjonsnivå. En effektiv arbeidsflyt for utforskende dataanalyse må kritisk identifisere interessante mønstre og relasjoner, noe som blir stadig vanskeligere når dimensjonaliteten til dataene øker. Selv om dette delvis kan løses med eksisterende reduksjonsteknikker er det alltid en fare for at subtile mønstre kan gå tapt i reduksjonsprosessen. Isteden presenterer vi i studien DimLift, en iterativ dimensjonsreduksjonsteknikk som muliggjør brukeridentifikasjon av interessante mønstre og relasjoner som kan ligge subtilt i et datasett gjennom dimensjonale bunter. Nøkkelen til denne metoden er brukerens evne til å styre dimensjonalitetsreduksjonen slik at den følger brukerens egne undersøkelseslinjer. For videre å undersøke kommunikasjon til eksperter og ikke-eksperter, studeres i neste arbeid utformingen av visualiseringer for kommunikasjon til publikum med ulike nivåer av ekspertnivå. Det er naturlig å forvente at eksperter innen et emne kan ha ulike preferanser og kriterier for å vurdere en visuell kommunikasjon i forhold til et ikke-ekspertpublikum. Dette påvirker hvor effektivt et bilde kan benyttes til å formidle en gitt scenario. Med utgangspunkt i ulike teknikker innen biomedisinsk illustrasjon og visualisering, gjennomførte vi derfor en utforskende studie av kriteriene som publikum bruker når de evaluerer en biomedisinsk prosessvisualisering målrettet for kommunikasjon. Fra denne studien identifiserte vi muligheter for ytterligere konvergens av biomedisinsk illustrasjon og visualiseringsteknikker for mer målrettet visuell kommunikasjonsdesign. Særlig beskrives i større dybde utviklingen av semantisk konsistente retningslinjer for farging av molekylære scener. Hensikten med slike retningslinjer er å heve den vitenskapelige kompetansen til ikke-ekspertpublikum innen molekyler visualisering, som vil være spesielt relevant for kommunikasjon til befolkningen i forbindelse med folkehelseopplysning. All kode og empiriske funn utviklet i arbeidet med denne avhandlingen er åpen kildekode og tilgjengelig for gjenbruk av det vitenskapelige miljøet og offentligheten. Metodene og funnene presentert i denne avhandlingen danner et grunnlag for tverrfaglig biomedisinsk illustrasjon og visualiseringsforskning, og åpner flere muligheter for fortsatt arbeid med visualisering av fysiologiske prosesser.The overarching theme of this thesis is the cross-disciplinary application of medical illustration and visualization techniques to address challenges in exploring, analyzing, and communicating aspects of physiology to audiences with differing expertise. Describing the myriad biological processes occurring in living beings over time, the science of physiology is complex and critical to our understanding of how life works. It spans many spatio-temporal scales to combine and bridge the basic sciences (biology, physics, and chemistry) to medicine. Recent years have seen an explosion of new and finer-grained experimental and acquisition methods to characterize these data. The volume and complexity of these data necessitate effective visualizations to complement standard analysis practice. Visualization approaches must carefully consider and be adaptable to the user's main task, be it exploratory, analytical, or communication-oriented. This thesis contributes to the areas of theory, empirical findings, methods, applications, and research replicability in visualizing physiology. Our contributions open with a state-of-the-art report exploring the challenges and opportunities in visualization for physiology. This report is motivated by the need for visualization researchers, as well as researchers in various application domains, to have a centralized, multiscale overview of visualization tasks and techniques. Using a mixed-methods search approach, this is the first report of its kind to broadly survey the space of visualization for physiology. Our approach to organizing the literature in this report enables the lookup of topics of interest according to spatio-temporal scale. It further subdivides works according to any combination of three high-level visualization tasks: exploration, analysis, and communication. This provides an easily-navigable foundation for discussion and future research opportunities for audience- and task-appropriate visualization for physiology. From this report, we identify two key areas for continued research that begin narrowly and subsequently broaden in scope: (1) exploratory analysis of multifaceted physiology data for expert users, and (2) communication for experts and non-experts alike. Our investigation of multifaceted physiology data takes place over two studies. Each targets processes occurring at different spatio-temporal scales and includes a case study with experts to assess the applicability of our proposed method. At the molecular scale, we examine data from magnetic resonance spectroscopy (MRS), an advanced biochemical technique used to identify small molecules (metabolites) in living tissue that are indicative of metabolic pathway activity. Although highly sensitive and specific, the output of this modality is abstract and difficult to interpret. Our design study investigating the tasks and requirements for expert exploratory analysis of these data led to SpectraMosaic, a novel application enabling domain researchers to analyze any permutation of metabolites in ratio form for an entire cohort, or by sample region, individual, acquisition date, or brain activity status at the time of acquisition. A second approach considers the exploratory analysis of multidimensional physiological data at the opposite end of the spatio-temporal scale: population. An effective exploratory data analysis workflow critically must identify interesting patterns and relationships, which becomes increasingly difficult as data dimensionality increases. Although this can be partially addressed with existing dimensionality reduction techniques, the nature of these techniques means that subtle patterns may be lost in the process. In this approach, we describe DimLift, an iterative dimensionality reduction technique enabling user identification of interesting patterns and relationships that may lie subtly within a dataset through dimensional bundles. Key to this method is the user's ability to steer the dimensionality reduction technique to follow their own lines of inquiry. Our third question considers the crafting of visualizations for communication to audiences with different levels of expertise. It is natural to expect that experts in a topic may have different preferences and criteria to evaluate a visual communication relative to a non-expert audience. This impacts the success of an image in communicating a given scenario. Drawing from diverse techniques in biomedical illustration and visualization, we conducted an exploratory study of the criteria that audiences use when evaluating a biomedical process visualization targeted for communication. From this study, we identify opportunities for further convergence of biomedical illustration and visualization techniques for more targeted visual communication design. One opportunity that we discuss in greater depth is the development of semantically-consistent guidelines for the coloring of molecular scenes. The intent of such guidelines is to elevate the scientific literacy of non-expert audiences in the context of molecular visualization, which is particularly relevant to public health communication. All application code and empirical findings are open-sourced and available for reuse by the scientific community and public. The methods and findings presented in this thesis contribute to a foundation of cross-disciplinary biomedical illustration and visualization research, opening several opportunities for continued work in visualization for physiology.Doktorgradsavhandlin

Virtual and Augmented Reality Techniques for Minimally Invasive Cardiac Interventions: Concept, Design, Evaluation and Pre-clinical Implementation

While less invasive techniques have been employed for some procedures, most intracardiac interventions are still performed under cardiopulmonary bypass, on the drained, arrested heart. The progress toward off-pump intracardiac interventions has been hampered by the lack of adequate visualization inside the beating heart. This thesis describes the development, assessment, and pre-clinical implementation of a mixed reality environment that integrates pre-operative imaging and modeling with surgical tracking technologies and real-time ultrasound imaging. The intra-operative echo images are augmented with pre-operative representations of the cardiac anatomy and virtual models of the delivery instruments tracked in real time using magnetic tracking technologies. As a result, the otherwise context-less images can now be interpreted within the anatomical context provided by the anatomical models. The virtual models assist the user with the tool-to-target navigation, while real-time ultrasound ensures accurate positioning of the tool on target, providing the surgeon with sufficient information to ``see\u27\u27 and manipulate instruments in absence of direct vision. Several pre-clinical acute evaluation studies have been conducted in vivo on swine models to assess the feasibility of the proposed environment in a clinical context. Following direct access inside the beating heart using the UCI, the proposed mixed reality environment was used to provide the necessary visualization and navigation to position a prosthetic mitral valve on the the native annulus, or to place a repair patch on a created septal defect in vivo in porcine models. Following further development and seamless integration into the clinical workflow, we hope that the proposed mixed reality guidance environment may become a significant milestone toward enabling minimally invasive therapy on the beating heart

혈관 구조 분석 기반 혈류선 추출과 불투명도 변조를 이용한 혈류 가시화 기법

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2016. 2. 신영길.With recent advances in acquisition and simulation of blood flow data, blood flow visualization has been widely used in medical imaging for the diagnosis and treatment of pathological vessels. The integral line based method has been most commonly employed to depict hemodynamic data because it exhibits a long term flow behavior useful for flow analysis. This method generates integral lines to be used as a basis for graphical representation by tracing the trajectory of a massless particle released on the vector field through a numerical integration. However, there are several unsolved problems when this previous method is applied to thin curved vascular structures. The first one is to locate a seeding plane, which is manually performed in the existing methods, thus yielding inconsistent visual results. The second one is the early termination of a line integration due to locally reversed flow and narrow tubular structure, which results in short flowlines comparing with the vessel length. And the last one is the line occlusion caused by the dense depiction of flowlines. Additionally, in blood flow visualization for clinical uses, it is essential to apparently exhibit abnormal flow relevant to vessel diseases. In this paper, we present an enhanced method that overcomes problems related to the integration based flow visualization and depicts hemodynamics in a more informative way for assisting the diagnosis process. Using the fact that blood flow passes through the inlet or outlet but is blocked by vessel wall, we firstly identify the vessel inlet or outlet by the orthogonality metric between flow velocity vector and vessel surface normal vector. Then, we generate seed points on the detected inlet or outlet by Poisson disk sampling. Therefore, we can achieve the automatic seeding that leads to a consistent and faster flow depiction by skipping the manual location of a seeding plane to initiate the line integration. In addition, we resolve the early terminated line integration by applying the tracing direction adaptively based on flow direction at each seed point and by performing the additional seeding near the terminated location. This solution enables to yield length-extended flowlines, which contribute to faithful flow visualization. Based on the observation that blood flow usually follows the vessel track if there is no obstacle or leak in the middle of a passage, we define the representative flowline for each branch by the vessel centerline. Then, we render flowlines by assigning the opacity according to their shape similarity with the vessel centerline so that flowlines similar to the vessel centerline are shown transparently, while different ones opaquely. Accordingly, our opacity modulation method enables flowlines with unusual flow pattern to appear more noticeable, while minimizing visual clutter and line occlusion. Finally, we introduce HSV (hue, saturation, value) color coding to simultaneously exhibit flow attributes such as local speed and residence time. This color coding gives a more realistic fading effect on the older particles or line segments by attenuating the saturation according to the residence time. Hence, it supports users in comprehending intuitively multiple information at once. Experimental results show that our technique is well suitable to depict blood flow in vascular structures.Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Problem Statement 3 1.3 Main Contribtion 7 1.4 Organization of the Dissertation 8 Chapter 2 Related Works 9 2.1 Flow and Velocity Vector 9 2.2 Flow Visualization 10 2.3 Blood Flow Visualization 16 2.3.1 Geometric Method 16 2.3.2 Feature-Based Method 18 2.3.3 Partition-Based Method 19 Chapter 3 Integration based Flowline Extraction 22 3.1 Overview 22 3.2 Seeding 23 3.3 Barycentric Coordinate Conversion 24 3.4 Cell Searching 26 3.5 Velocity Vector Calculation 27 3.6 Advection 28 3.7 Step Size Adaptation 30 Chapter 4 Blood Flow Visualization using Flow and Geometric Analysis 32 4.1 Preprocessing 33 4.2 Inlet or Outlet based Seeding 35 4.3 Tracing 39 4.3.1 Flow based Bidirectional Tracing 39 4.3.2 Additional Seeding for Length Extended Line Integration 41 4.4 Opacity Modulation 43 4.4.1 Global Opacity 45 4.4.2 Local Opacity 46 4.4.3 Opacity Adjustment 52 4.4.4 Blending 53 4.5 HSV Color Coding 54 4.6 Vessel Rendering 58 4.6.1 Vessel Smoothing 59 4.6.2 Vessel Contour Enhancement 60 4.7 Flowline Drawing 61 4.7.1 Line Illumination 61 4.7.2 Line Halo 63 4.8 Animation 64 Chapter 5 Experimental Results 67 5.1 Evaluation on Seeding 69 5.2 Evaluation on Tracing 74 5.3 Evaluation on Opacity Modulation 82 5.4 Parameter Study 85 Chapter 6 Conclusion 87 Bibliography 89 초 록 99Docto

Interactive Visualization of Multimodal Brain Connectivity: Applications in Clinical and Cognitive Neuroscience

Magnetic resonance imaging (MRI) has become a readily available prognostic and diagnostic method, providing invaluable information for the clinical treatment of neurological diseases. Multimodal neuroimaging allows integration of complementary data from various aspects such as functional and anatomical properties; thus, it has the potential to overcome the limitations of each individual modality. Specifically, functional and diffusion MRI are two non-invasive neuroimaging techniques customized to capture brain activity and microstructural properties, respectively. Data from these two modalities is inherently complex, and interactive visualization can assist with data comprehension. The current thesis presents the design, development, and validation of visualization and computation approaches that address the need for integration of brain connectivity from functional and structural domains. Two contexts were considered to develop these approaches: neuroscience exploration and minimally invasive neurosurgical planning. The goal was to provide novel visualization algorithms and gain new insights into big and complex data (e.g., brain networks) by visual analytics. This goal was achieved through three steps: 3D Graphical Collision Detection: One of the primary challenges was the timely rendering of grey matter (GM) regions and white matter (WM) fibers based on their 3D spatial maps. This challenge necessitated pre-scanning those objects to generate a memory array containing their intersections with memory units. This process helped faster retrieval of GM and WM virtual models during the user interactions. Neuroscience Enquiry (MultiXplore): A software interface was developed to display and react to user inputs by means of a connectivity matrix. This matrix displays connectivity information and is capable to accept selections from users and display the relevant ones in 3D anatomical view (with associated anatomical elements). In addition, this package can load multiple matrices from dynamic connectivity methods and annotate brain fibers. Neurosurgical Planning (NeuroPathPlan): A computational method was provided to map the network measures to GM and WM; thus, subject-specific eloquence metric can be derived from related resting state networks and used in objective assessment of cortical and subcortical tissue. This metric was later compared to apriori knowledge based decisions from neurosurgeons. Preliminary results show that eloquence metric has significant similarities with expert decisions

Shear-promoted drug encapsulation into red blood cells: a CFD model and μ-PIV analysis

The present work focuses on the main parameters that influence shear-promoted encapsulation of drugs into erythrocytes. A CFD model was built to investigate the fluid dynamics of a suspension of particles flowing in a commercial micro channel. Micro Particle Image Velocimetry (μ-PIV) allowed to take into account for the real properties of the red blood cell (RBC), thus having a deeper understanding of the process. Coupling these results with an analytical diffusion model, suitable working conditions were defined for different values of haematocrit