Fuzzy image enhancement and associative feature matching in radiotherapy

G. Krell, H. R. Tizhoosh, T. Lilienblum, C. J. Moore, B. Michaelis

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The electronic portal imaging device has become an important tool for the clinician to verify the shape and the location of the therapy beam with respect to the patient's anatomy. Normally, a visual comparison of the real patient position related to the beam with the planned treatment field is performed. This treatment field is defined during diagnostics and treatment planning. For this purpose, a treatment simulation takes place as a result of which a simulator image (SI) is captured. Because of the imaging physics the unprocessed electronic portal images (EPIs) are very poor in quality compared with the SI that is usually an X-ray image from CT. The conventional EPI allows only a rough verification of patient position relative to bony structures. The state of the art conventional enhancement techniques can be applied to EPIs to give some improvement for further visual analysis after the treatment (off-line). This paper presents an approach that combines an associative restoration algorithm with a fuzzy image enhancement technique to reach a new quality. The main idea of the associative restoration is the merger of the EPI with the SI to generate a much better in-treatment image than obtained by simple enhancement and to allow a more reliable feature matching. Firstly, the images are enhanced by the fuzzy image enhancement as a result of which the visibility of structures like bones is improved. This is important also for the following alignment of corresponding structures in the images. A specially structured artificial neural network that we call modified associative memory is trained by the enhanced SI.

Original languageEnglish (US)
Title of host publication1997 IEEE International Conference on Neural Networks, ICNN 1997
Number of pages6
StatePublished - 1997
Event1997 IEEE International Conference on Neural Networks, ICNN 1997 - Houston, TX, United States
Duration: Jun 9 1997Jun 12 1997

Publication series

NameIEEE International Conference on Neural Networks - Conference Proceedings
ISSN (Print)1098-7576


Conference1997 IEEE International Conference on Neural Networks, ICNN 1997
Country/TerritoryUnited States
CityHouston, TX

ASJC Scopus subject areas

  • Software


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