Project

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Optical tomography: novel spline algorithms and application in mice and man

Applicant Hunziker Patrick
Number 160178
Funding scheme Project funding (Div. I-III)
Research institution Klinik für Intensivmedizin Universitätsspital Basel
Institution of higher education University of Basel - BS
Main discipline Mathematics
Start/End 01.04.2015 - 30.09.2018
Approved amount 208'143.00
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All Disciplines (4)

Discipline
Mathematics
Electrical Engineering
Experimental Cancer Research
Information Technology

Keywords (8)

medical imaging; light propagation model; fluorescent nanomaterials; spline discretization; tensor algebra; image reconstruction; molecular imaging; optical tomography

Lay Summary (German)

Lead
Zur Verbesserung des neuartigen, schonenden medizinischen Bildgebungsverfahrens "optische Diffusionstomographie" werden neue mathematische Methoden entwickelt und in kompakten und kostengünstigen Rechnerplatformen umgesetzt.
Lay summary

Die optische Diffusions-Tomographie ist ein medizinisches Bildgebungsverfahren, welches ohne Röntgenstrahlen, ohne radioaktive Materialien und ohne sehr teure Geräte Krankheitsprozesse im Körper sichtbar machen kann.

Allerdings ist diese neuartige Technologie mathematisch herausfordernd: die Berechnung der Bilder setzt häufig grobe Vereinfachungen voraus.

In diesem Projekt werden durch Entwicklung spezieller mathematischer Methoden (Splines), deren Umsetzung auf neuartigen Rechner-Architekturen (FPGA="Field Programmable Gate Arrays") sowie biomedizinischer Testung neue Wege gesucht, diese schonende Bildgebungstechnik für die Patienten der Zukunft präziser und im klinischen Alltag verfügbarer zu machen.


Direct link to Lay Summary Last update: 23.06.2015

Responsible applicant and co-applicants

Employees

Publications

Publication
МЕТОД ГОЛОГРАФИЧЕСКОГО ПОСТРОЕНИЯ ИЗОБРАЖЕНИЯ НЕОДНОРОДНОСТЕЙ ПЛОТНОСТИ ВЕЩЕСТВА ПОЛУПРОЗРАЧНОЙ СРЕДЫ С ИСПОЛЬЗОВАНИЕМ ПЛОСКОПАРАЛЛЕЛЬНОГО ЛАЗЕРНОГО ИЗЛУЧЕНИЯ
Hunziker Patrick, Kravchenko V.F., Morozov Alexey V., Volosyuk E.V., Volosyuk V.K., Zhyla S.S. (2017), МЕТОД ГОЛОГРАФИЧЕСКОГО ПОСТРОЕНИЯ ИЗОБРАЖЕНИЯ НЕОДНОРОДНОСТЕЙ ПЛОТНОСТИ ВЕЩЕСТВА ПОЛУПРОЗРАЧНОЙ СРЕДЫ С ИСПОЛЬЗОВАНИЕМ ПЛОСКОПАРАЛЛЕЛЬНОГО ЛАЗЕРНОГО ИЗЛУЧЕНИЯ, in ФИЗИЧЕСКИЕ ОСНОВЫ ПРИБОРОСТРОЕНИЯ, 6(1), 34-49.
A Compute Model for Generating High Performance Computing SoCs on Hybrid Systems with FPGAs
FriedrichFelix, MorozovOleksii (2016), A Compute Model for Generating High Performance Computing SoCs on Hybrid Systems with FPGAs, in FSP 2016; Third International Workshop on FPGAs for Software Programmers, LausanneIEEE, Lausanne.
ИССЛЕДОВАНИЕ МЕТОДА ГОЛОГРАФИЧЕСКОЙ ОЦЕНКИ РАСПРЕДЕЛЕНИЯ НЕОДНОРОДНОСТЕЙ ПЛОТНОСТИ ВЕЩЕСТВА В ПОЛУПРОЗРАЧНЫХ СРЕДАХ
HunzikerPatrick, Kravchenko V.F., MorozovAlexey V., Volosyuk E.V., VolosyukV.K., ZhylaS.S. (2016), ИССЛЕДОВАНИЕ МЕТОДА ГОЛОГРАФИЧЕСКОЙ ОЦЕНКИ РАСПРЕДЕЛЕНИЯ НЕОДНОРОДНОСТЕЙ ПЛОТНОСТИ ВЕЩЕСТВА В ПОЛУПРОЗРАЧНЫХ СРЕДАХ, in ФИЗИЧЕСКИЕ ОСНОВЫ ПРИБОРОСТРОЕНИЯ, 5(3), 78-91.

Collaboration

Group / person Country
Types of collaboration
Biomedical Data Analysis Group, Prof. Volker Roth, Uni Basel Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
National Aerospace University, Ukraine (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Department of Computer Science, ETH Zuerich Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication

Patents

Title Date Number Inventor Owner

Abstract

Optical tomographic (OT) imaging of tissue distribution of medical nanomaterials ("molecular imaging")  and of tissue function ("functional imaging") are promising noninvasive modalities for biomedical research and clinical application. However, application of these novel technologies faces technical challenges related to suited materials and to very large computational requirements.We have recently reported highly efficient spline-based algorithms for multidimensional signal reconstruction and successfully applied them to clinical images acquired by ultrasound, computed tomography and magnetic resonance imaging, documenting high reconstruction quality and high computational efficiency.The goal of the project is to develop novel, spline-based algorithms for improved performance and quality in optical tomography and to explore their potential in a prototypic setup for imaging in experimental animals and in man.Specifically, the project is aimed at:- Development of highly efficient solving algorithms for 3-D optical tomographic imaging using the mathematics of splines and mathematical modelling of light propagation in tissue to boost the performance of OT imaging and make it practical for use in experimental and clinical embedded imaging systems.- Establishing an experimental setup suited for acquisition of optical tomographic measurements in mice and man.- Validation of the developed spline-based solving algorithms on simulated data and on phantom data acquired by an acquisition setup to characterise the performance of tomographic reconstruction.- Testing the applicability of the developed spline-based solving algorithms using real data acquired from mice.- Initial exploration of the applicability of the developed spline-based solving algorithms using real data acquired from normal volunteers and stroke patients.The stated aims are to be achieved with the following methods:- Spline-based modelling of light propagation in the tissue- Spline-based variational image reconstruction- Computational tensor algebra- Validation by synthetic data, phantom data and clinical imaging
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