Skip to main content

The role of image fusion in diagnostic imaging for stereotactic neurosurgery and radiosurgery/stereotactic radiotherapy

  • Conference paper
Schädelbasischirurgie

Abstract

In general, image fusion quality depends on the used data sets being determined by the performance of the imaging systems resp. the scan protocols. Powerful image fusion systems are capable to superimpose various CT and MRI data sets, in some cases PET, SPECT and fMRT data sets, too [5, 6, 7, 9, 13]. The respective data sets must be acquired in accordance to the software requirements and transferred lossless to the workstation via LAN or by means of a CD-ROM.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 74.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Betti O, Galmarini D, Derechinskiy V (1991) Radiosurgery with a linear accelerator. Methodological aspects. Stereotact Funct Neurosurg 57: 87–98

    Article  CAS  Google Scholar 

  2. Burkhardt S, Schweikard A, Burkart R (2003) Numerical determination of the susceptibility caused geometric distortions in magnetic resonance imaging. Med Image Anal 7: 221–236

    Article  PubMed  Google Scholar 

  3. D’Ambrosio A, Bruce J (2003) Treatment of meningioma: an update. Curr Neurol Neurosci Rep 3: 206–214

    Article  PubMed  Google Scholar 

  4. Grebe G, Pfaender M, Roll M (2001) Dynamic arc radiosurgery and radiotherapy: commissioning and verification of dose distributions. Int J Radiat Oncol Biol Phys 51: 1451–1460

    Article  Google Scholar 

  5. Grosu A, Lachner R, Wiedenmann N (2003) Validation of a method for automatic image fusion (Brain LAB System) of CT data and 11C-methionine-PET data for stereotactic radiotherapy using a LINAC: first clinical experience. Int J Radiat Oncol Biol Phys 56: 1450–1463

    Article  PubMed  Google Scholar 

  6. Hamm K, Przetak Ch, Kleinert G, Surber G, Schmücking M, Baum RP (2001) Netz-ge-stützter Datentransfer für die automatische Bildfusion von metabolischer (PET) und morphologischer (CT/MRT) Bildgebung in der Radiochirurgie/stereotaktischen Radiotherapie. In: Jäckel A (Hrsg) Telemedizin-führer Deutschland, Ober-Mörlen, Ausgabe 2002, S 162–165

    Google Scholar 

  7. Henze M, Mohammed A, Schlemmer H (2002) Detection of tumour progression in the follow-up of irradiated low-grade astrocytomas: comparison of 3-[123I]iodo-alpha-methyl-L-tyrosine and 99mTc-MIBI SPECT. Eur J Nucl Med Mol Imaging 29: 1455–1461

    Article  PubMed  Google Scholar 

  8. Hill DL, Batchelor PG, Holden M, Hawkes DJ (2001) Medical image registration. Phys Med Biol 46: R1–R45

    Article  PubMed  CAS  Google Scholar 

  9. Jaradat HA, Tome WA, McNutt TR, Meye-rand ME (2003) On the incorporation of multi-modality image registration into the radiotherapy treatment planning process. Technol Cancer Res Treatment 2: 1–8

    Google Scholar 

  10. Kapur T, Grimson E, Wells W, Kikinis R (1996) Segmentation of brain tissue from magnetic resonance images. Med Image Anal 1: 109–127

    Article  PubMed  CAS  Google Scholar 

  11. Mutic S, Dempsey JF, Bosch WR, Low DA, Drzymala RE, Chao KSC, Goddu SM, Cutler PD, Purdy JA (2001) Multimodality image registration quality assurance for conformai three-dimensional treatment planning. Int J Rad Oncol Biol Phys 51: 255–260

    Article  CAS  Google Scholar 

  12. Ross D, Sandler H, Balter J (2002) Imaging changes after stereotactic radiosurgery of primary and secondary malignant brain tumors. J Neurooncol 56: 175–181

    Article  PubMed  Google Scholar 

  13. Schmücking M, Baum R, Przetak C, Niesen A, Surber G, Kleinert G, Hamm K, Lopatta E, Wendt T (2001) Potentieller Nutzen einer Bildfusion von metabolischer (PET) mit morphologischer (CT/MRT) Bildgebung in der Bestrahlungsplanung. Strahlenther Onkol 177(Sondernr 1): 6

    Google Scholar 

  14. Solberg T, Fogg R, Selch M (2000) Conformal radiosurgery using a dedicated linac and micro multileaf collimator. Radiosurgery 3: 53–63

    Article  Google Scholar 

  15. Studholme C, Hill D, Hawkes D (1996) Automated 3-D registration of MR and CT images of the head. Med Image Anal 1: 163–175

    Article  PubMed  CAS  Google Scholar 

  16. Wells W, Viola P, Atsumi H, Nakajima S, Kikinis R (1996) Multi-modal volume registration by maximization of mutual information. Med Image Anal 1: 35–51

    Article  PubMed  Google Scholar 

  17. Williams J (2002) Fractionated stereotactic radiotherapy for acoustic neuromas. Stereotact Funct Neurosurg 78: 17–28

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to K. Hamm .

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Wien

About this paper

Cite this paper

Hamm, K. et al. (2004). The role of image fusion in diagnostic imaging for stereotactic neurosurgery and radiosurgery/stereotactic radiotherapy. In: Schädelbasischirurgie. Springer, Vienna. https://doi.org/10.1007/978-3-7091-0622-8_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-7091-0622-8_5

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-22324-6

  • Online ISBN: 978-3-7091-0622-8

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics