IEEE J Biomed Health Inform - A spatiotemporal-based scheme for efficient registration-based segmentation of thoracic 4-D MRI.

Tópicos

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Resumo

Dynamic three-dimensional (3-D) (four-dimensional, 4-D) magnetic resonance (MR) imaging is gaining importance in the study of pulmonary motion for respiratory diseases and pulmonary tumor motion for radiotherapy. To perform quantitative analysis using 4-D MR images, segmentation of anatomical structures such as the lung and pulmonary tumor is required. Manual segmentation of entire thoracic 4-D MRI data that typically contains many 3-D volumes acquired over several breathing cycles is extremely tedious, time consuming, and suffers high user variability. This requires the development of new automated segmentation schemes for 4-D MRI data segmentation. Registration-based segmentation technique that uses automatic registration methods for segmentation has been shown to be an accurate method to segment structures for 4-D data series. However, directly applying registration-based segmentation to segment 4-D MRI series lacks efficiency. Here we propose an automated 4-D registration-based segmentation scheme that is based on spatiotemporal information for the segmentation of thoracic 4-D MR lung images. The proposed scheme saved up to 95% of computation amount while achieving comparable accurate segmentations compared to directly applying registration-based segmentation to 4-D dataset. The scheme facilitates rapid 3-D/4-D visualization of the lung and tumor motion and potentially the tracking of tumor during radiation delivery.

Resumo Limpo

dynam threedimension d fourdimension d magnet reson mr imag gain import studi pulmonari motion respiratori diseas pulmonari tumor motion radiotherapi perform quantit analysi use d mr imag segment anatom structur lung pulmonari tumor requir manual segment entir thorac d mri data typic contain mani d volum acquir sever breath cycl extrem tedious time consum suffer high user variabl requir develop new autom segment scheme d mri data segment registrationbas segment techniqu use automat registr method segment shown accur method segment structur d data seri howev direct appli registrationbas segment segment d mri seri lack effici propos autom d registrationbas segment scheme base spatiotempor inform segment thorac d mr lung imag propos scheme save comput amount achiev compar accur segment compar direct appli registrationbas segment d dataset scheme facilit rapid dd visual lung tumor motion potenti track tumor radiat deliveri

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