Miriam H. A. Bauer

CV
3papers
14citations
Novelty32%
AI Score17

3 Papers

CVFeb 5, 2016
Preoperative Volume Determination for Pituitary Adenoma

Dzenan Zukic, Jan Egger, Miriam H. A. Bauer et al.

The most common sellar lesion is the pituitary adenoma, and sellar tumors are approximately 10-15% of all intracranial neoplasms. Manual slice-by-slice segmentation takes quite some time that can be reduced by using the appropriate algorithms. In this contribution, we present a segmentation method for pituitary adenoma. The method is based on an algorithm that we have applied recently to segmenting glioblastoma multiforme. A modification of this scheme is used for adenoma segmentation that is much harder to perform, due to lack of contrast-enhanced boundaries. In our experimental evaluation, neurosurgeons performed manual slice-by-slice segmentation of ten magnetic resonance imaging (MRI) cases. The segmentations were compared to the segmentation results of the proposed method using the Dice Similarity Coefficient (DSC). The average DSC for all datasets was 75.92% +/- 7.24%. A manual segmentation took about four minutes and our algorithm required about one second.

CVOct 23, 2013
A Ray-based Approach for Boundary Estimation of Fiber Bundles Derived from Diffusion Tensor Imaging

Miriam H. A. Bauer, Sebastiano Barbieri, Jan Klein et al.

Diffusion Tensor Imaging (DTI) is a non-invasive imaging technique that allows estimation of the location of white matter tracts in-vivo, based on the measurement of water diffusion properties. For each voxel, a second-order tensor can be calculated by using diffusion-weighted sequences (DWI) that are sensitive to the random motion of water molecules. Given at least 6 diffusion-weighted images with different gradients and one unweighted image, the coefficients of the symmetric diffusion tensor matrix can be calculated. Deriving the eigensystem of the tensor, the eigenvectors and eigenvalues can be calculated to describe the three main directions of diffusion and its magnitude. Using DTI data, fiber bundles can be determined, to gain information about eloquent brain structures. Especially in neurosurgery, information about location and dimension of eloquent structures like the corticospinal tract or the visual pathways is of major interest. Therefore, the fiber bundle boundary has to be determined. In this paper, a novel ray-based approach for boundary estimation of tubular structures is presented.

CVOct 21, 2013
Determination, Calculation and Representation of the Upper and Lower Sealing Zones During Virtual Stenting of Aneurysms

Jan Egger, Miriam H. A. Bauer, Stefan Großkopf et al.

In this contribution, a novel method for stent simulation in preoperative computed tomography angiography (CTA) acquisitions of patients is presented where the sealing zones are automatically calculated and visualized. The method is eligible for non-bifurcated and bifurcated stents (Y-stents). Results of the proposed stent simulation with an automatic calculation of the sealing zones for specific diseases (abdominal aortic aneurysms (AAA), thoracic aortic aneurysms (TAA), iliac aneurysms) are presented. The contribution is organized as follows. Section 2 presents the proposed approach. In Section 3, experimental results are discussed. Section 4 concludes the contribution and outlines areas for future work.