Automatic segmentation of brain hemispheres by midplane detection in class images

Gudrun Wagenknecht; Hans-Juergen Kaiser; Osama Sabri; Udalrich Buell

doi:10.1117/12.387611

6 June 2000 Automatic segmentation of brain hemispheres by midplane detection in class images

Gudrun Wagenknecht, Hans-Juergen Kaiser, Osama Sabri, Udalrich Buell

Proceedings Volume 3979, Medical Imaging 2000: Image Processing; (2000) https://doi.org/10.1117/12.387611
Event: Medical Imaging 2000, 2000, San Diego, CA, United States

Abstract

Segmentation of brain hemispheres is necessary to study left- right differences in structure and function. For extraction of a 3D individual region-of-interest atlas of the human brain, detection of the midplane is the sine qua non as it provides the reference plane for determining other anatomical objects. Extraction of the sagittal midplane is done in two main steps. First, a 2D filter is used to give a first approximation of the midplane position. To model symmetry properties of the midplane neighborhood, the different filter columns contain class-dependent weights for cerebrospinal fluid, gray and white matter. The filter can be rotated in a range of angles. In a user-defined range of planes, the global maximum of the filter response is searched for and the resulting position is utilized to restrict the search in the remaining planes. In a second step, midplane extraction is refined by searching for the optimal path of the midplane within the filter mask at optimum position. Symmetry properties are modeled analogous to the first step with class-dependent weights of the filter columns. The extraction of the midplane gives accurate and reliable results in simulated data sets and patient studies even if asymmetric artifacts are simulated.

Citation Download Citation

Gudrun Wagenknecht, Hans-Juergen Kaiser, Osama Sabri, and Udalrich Buell "Automatic segmentation of brain hemispheres by midplane detection in class images", Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); https://doi.org/10.1117/12.387611

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