Medical image processing and finite element analysis
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Medical image processing and finite element analysis. András Hajdu UNIVERSITY OF DEBRECEN HUNGARY. SSIP 2003 July 3-12 , 2003 Timişoara, Romania. MEDIP Platform independent software system for medical image processing.

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Medical image processing and finite element analysis

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Medical image processing and finite element analysis

András Hajdu



SSIP 2003

July 3-12, 2003

Timişoara, Romania

MEDIPPlatformindependent software system for medical imageprocessing

The aim of the project is to develop an informatical background to theoretical and applied studies in the field of multi-modal medical image processing,which results may lead to

marketable products.


Test partners

  • Department of Information Technology,University of Debrecen

  • PET Center,

    University of Debrecen

  • Mediso Medical Imaging System Ltd.

  • Department of Orthopedic Surgery,University of Debrecen

  • Faculty of Health Sciences, Chair of Radiotherapy,Semmelweis University

  • Faculty of Medicine Dept. of Radiology and Oncotherapy,Semmelweis University

MEDIPPlatformindependent software system for medical imageprocessing

MEDIPPlatformindependent software system for medical imageprocessing




  • Survey, problem specification

  • Modelling, system plans

  • Implementation

  • Implementation,optimisation

  • Fine tuning,testing, presentation

Pert diagram


finished sessions

current session






future sessions


MEDIP – Demostration programsPlatformindependent software system for medical imageprocessing

Finite element modelling

for virtual surgery

Selection of volume of interest based on image fusion

4D visualization of gated heart and lung inspections

Demonstration program

Finite element modelingfor virtual surgery

Dept. of Information Tech., UD

Dept. of Orthopaedy, UD

Demonstration program

Finite element modelingfor virtual surgery

Connecting to the base libraries

  • File I/O (DICOM)

  • Segmentation techniques

  • Contour tracking, ROI selection

  • Morphological operations

  • Complex GUI

  • ROI and VOI 2D/3D visualization

  • 3D geometric navigation

  • Printing

Demonstration program

FEM surgery planning frame program

Login (database opening)

Launching (opening new/existing profile)

DICOM file import

Image manipulation (morphological filtering)

Segmentation (automatic/manual)

Creating geometric model

Demonstration program

Surgery planning (virtual osteotomy)

Adjusting parameters

FEM contact

3D visualization, selecting VOI

Surgery planning (virtual osteotomy)Case study


Zoltán Csernátony, Department of Orthopaedics, UD

Szabolcs Molnár, Department of Orthopaedics, UD

Sándor Manó, College Faculty of Engineering, UD

AndrásHajdu, Institute of Informatics, UD

ZoltánZörgő, Institute of Informatics, UD


Shorter femur

Shorter tibia

Orthopaedic shoes

Handling the problem (I.)

Surgical intervention(after Wagner and Ilizarov)



Handling the problem (II.)


A new lengthening method


  • Torsion and angulation could also be correnced

Potencial instrumentation

Past and present

  • In the past there existed no way of testing new interventions but to try it out in vivo

  • This days technology makes is possible to test and adjust new operative interventions before even one cut is made

Validating new ideas

  • Laboratory tests

  • Finite element analysis

How can we use FEM/FEA?

CT slices



Importing images in CT firmware format (DICOM)

Image enhancement (sharpening, filtering)

Extracting ROIs

Building up a basic model

Applying contour splines (Euclidean geometry)

Reconstructing solid model (Coons patches)

Building up a basic model

Based on the path of the cutting tool

We need to determine:

Cutting thickness


Ending hole parameters

Modeling intervention geometry (I.)

We subtract the object representing the „removed tissue” from the femur model

Modeling interventiongeometry (II.)

The bone tissue should be modeled as a very complicated nonlinear anisotropic material

We are using linearelasticizotropicandorthotropicmaterial models instead

We mesh the model

One end is fixed, on the other end a traction force is applied

How big is the evolved stress? How much elongation can it support?

Modeling intervention physics

Some results

There exists an optimal combination of parameter values

Additional adjustments

  • The greatest stress values evolve near the ending holes.

  • The inward oriented conical bore appears to be the most suitable

We have built a schematic model

It is a cylindrical pipe with inner and outer diameters equaling the femur’s average diameters

The same analysis were performed

Checking the results

  • The stress values measured on the pipe-model were 1.61 (D=0.27) times lower under same conditions

  • There was a 91% correlation between the two datasets

Future plans

  • More precise material modeling by using cylindrical layers, and other element types

  • In-vitro lab tests based on the results

Thank you for your attention.

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