MIDL 2021

International Conference on
Medical Imaging with Deep Learning
5. bis 7. Juli 2021

Integrated Segmentation and Non-Linear Registration for Organ Segmentation and Motion Field Estimation in 4D CT Data

TitelIntegrated Segmentation and Non-Linear Registration for Organ Segmentation and Motion Field Estimation in 4D CT Data
Publication TypeJournal Article
Year of Publication2009
AuthorsSchmidt-Richberg A., Handels H., Ehrhardt J.
JournalMethods of information in medicine
Date Published2009
Publication Languageeng
SchlüsselwörterArtifacts, Computer Simulation, Humans, Image Interpretation, Computer-Assisted, Liver, Movement, Numerical Analysis, Computer-Assisted, Phantoms, Imaging, Radiography, Abdominal, Radiography, Thoracic, Tomography, X-Ray Computed

OBJECTIVES: The development of spatiotemporal tomographic imaging techniques allows the application of novel techniques for diagnosis and therapy in the medical routine. However, in consequence to the increasing amount of image data automatic methods for segmentation and motion estimation are required. In adaptive radiation therapy, registration techniques are used for the estimation of respiration-induced motion of pre-segmented organs. In this paper, a variational approach for the simultaneous computation of segmentations and a dense non-linear registration of the 3D images of the sequence is presented.

METHODS: In the presented approach, a variational region-based level set segmentation of the structures of interest is combined with a diffusive registration of the spatial images of the sequence. We integrate both parts by defining a new energy term, which allows us to incorporate mutual prior information in order to improve the segmentation as well as the registration quality.

RESULTS: The presented approach was utilized for the segmentation of the liver and the simultaneous estimation of its respiration-induced motion based on four-dimensional thoracic CT images. For the considered patients, we were able to improve the results of the segmentation and the motion estimation, compared to the conventional uncoupled methods.

CONCLUSIONS: Applied in the field of radiation therapy of thoracic tumors, the presented integrated approach turns out to be useful for simultaneous segmentation and registration by improving the results compared to the application of the methods independently.

PubMed Link


Alternate JournalMethods Inf Med
Erstellt am 3. September 2012 - 14:03 von Kulbe. Zuletzt geändert am 15. April 2014 - 11:04 von Kulbe.


Medizinische Informatik
an der Uni Lübeck studieren

Informationen für
u. Einsteiger


Susanne Petersen

Tel+49 451 3101 5601
Fax+49 451 3101 5604

Gebäude 64 (Informatik)

Ratzeburger Allee 160
23538 Lübeck