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QUANTOM - improved tumor diagnosis by quantitative evaluation of tomography data using digital 3D image processing. Final report; QUANTOM - Verbesserung der Tumordiagnostik durch quantitative Auswertung von Tomographiedaten mit Hilfe der digitalen 3D-Bildverarbeitung. Abschlussbericht

Miscellaneous:

Abstract

Nonlinear techniques are applied to tasks in medical image processing. Using the so-called scaling index method and scaling vector method segmentation and detection algorithms are developed in order to recognise and measure tumors in three-dimensional tomographic data sets. It is shown that pulmonary nodules can well be detected in the lung only by analysing their morphological structure. Especially the nodules can be discriminated from the bronchovascular structures, which have the same intensity in the data sets. Newly developed segmentation algorithms, with which an exact volumetric assessment of tumors is made possible, are presented. It turns out that an algorithm, which combines elements from the watershed-transformation and from region growing techniques, yields the best results in terms of accuracy, transparency and reproducibility. The clinical valence of the volumetry is illustrated with studies concerning the response evaluation of tumors of the gastrointestinal tract during (chemo-)therapy. It turns out that the results obtained with an exact three-dimensional volume determination are in much better agreement with the histological gold standard than those obtained with simple conventional, planimetric measurements. Furthermore the specificity of the prediction for the response to a chosen therapy can be significantly increased using CT-volumetry and PET-measurements. Therefore, the number of therapeutically  More>>
Authors:
Publication Date:
Jul 01, 2001
Product Type:
Miscellaneous
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; NEOPLASMS; DIAGNOSIS; PATTERN RECOGNITION; IMAGE PROCESSING; ALGORITHMS; DATA PROCESSING; VOLUME; ACCURACY; POSITRON COMPUTED TOMOGRAPHY; SPECIFICITY; CLASSIFICATION; THREE-DIMENSIONAL CALCULATIONS; VALIDATION; COMPUTERIZED TOMOGRAPHY; PATIENTS; LUNGS
Sponsoring Organizations:
Bundesministerium fuer Bildung und Forschung, Berlin (Germany); DLR Deutsches Zentrum fuer Luft- und Raumfahrt e.V., Bonn (Germany)
OSTI ID:
20736987
Research Organizations:
Max-Planck-Institut fuer Extraterrestrische Physik, Garching (Germany); Klinikum rechts der Isar, Muenchen (Germany). Inst. fuer Roentgendiagnostik; Klinikum rechts der Isar, Muenchen (Germany). Inst. fuer Medizinische Statistik und Epidemiologie
Country of Origin:
Germany
Language:
German
Other Identifying Numbers:
Other: Foerderkennzeichen BMBF 50TT9731; TRN: DE06F6366
Availability:
Available from TIB Hannover: F02B1334
Submitting Site:
DEN
Size:
33 pages
Announcement Date:
Jun 16, 2006

Miscellaneous:

Citation Formats

Morfill, G. QUANTOM - improved tumor diagnosis by quantitative evaluation of tomography data using digital 3D image processing. Final report; QUANTOM - Verbesserung der Tumordiagnostik durch quantitative Auswertung von Tomographiedaten mit Hilfe der digitalen 3D-Bildverarbeitung. Abschlussbericht. Germany: N. p., 2001. Web.
Morfill, G. QUANTOM - improved tumor diagnosis by quantitative evaluation of tomography data using digital 3D image processing. Final report; QUANTOM - Verbesserung der Tumordiagnostik durch quantitative Auswertung von Tomographiedaten mit Hilfe der digitalen 3D-Bildverarbeitung. Abschlussbericht. Germany.
Morfill, G. 2001. "QUANTOM - improved tumor diagnosis by quantitative evaluation of tomography data using digital 3D image processing. Final report; QUANTOM - Verbesserung der Tumordiagnostik durch quantitative Auswertung von Tomographiedaten mit Hilfe der digitalen 3D-Bildverarbeitung. Abschlussbericht." Germany.
@misc{etde_20736987,
title = {QUANTOM - improved tumor diagnosis by quantitative evaluation of tomography data using digital 3D image processing. Final report; QUANTOM - Verbesserung der Tumordiagnostik durch quantitative Auswertung von Tomographiedaten mit Hilfe der digitalen 3D-Bildverarbeitung. Abschlussbericht}
author = {Morfill, G}
abstractNote = {Nonlinear techniques are applied to tasks in medical image processing. Using the so-called scaling index method and scaling vector method segmentation and detection algorithms are developed in order to recognise and measure tumors in three-dimensional tomographic data sets. It is shown that pulmonary nodules can well be detected in the lung only by analysing their morphological structure. Especially the nodules can be discriminated from the bronchovascular structures, which have the same intensity in the data sets. Newly developed segmentation algorithms, with which an exact volumetric assessment of tumors is made possible, are presented. It turns out that an algorithm, which combines elements from the watershed-transformation and from region growing techniques, yields the best results in terms of accuracy, transparency and reproducibility. The clinical valence of the volumetry is illustrated with studies concerning the response evaluation of tumors of the gastrointestinal tract during (chemo-)therapy. It turns out that the results obtained with an exact three-dimensional volume determination are in much better agreement with the histological gold standard than those obtained with simple conventional, planimetric measurements. Furthermore the specificity of the prediction for the response to a chosen therapy can be significantly increased using CT-volumetry and PET-measurements. Therefore, the number of therapeutically questionable operations can be reduced. Further possible fields of application for the newly developed methods are presented. (orig.)}
place = {Germany}
year = {2001}
month = {Jul}
}