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Julia Rackerseder

3 papers hereh-index 8217 citations14 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • eess.IV1

identity via Semantic Scholar / OpenAlex

most citedFully Automatic Segmentation of 3D Brain Ultrasound: Learning from Coarse Annotations

4 citations · 6 across the 2 of their papers we have counts for

collaborators

3 papers

cs.CV2019★ 4 cited

Fully Automatic Segmentation of 3D Brain Ultrasound: Learning from Coarse Annotations

Julia Rackerseder, Rüdiger Göbl, Nassir Navab +1

Intra-operative ultrasound is an increasingly important imaging modality in neurosurgery. However, manual interaction with imaging data during the procedures, for example to select…

cs.CV2019★ 2 cited

Weakly-Supervised White and Grey Matter Segmentation in 3D Brain Ultrasound

Beatrice Demiray, Julia Rackerseder, Stevica Bozhinoski +1

Although the segmentation of brain structures in ultrasound helps initialize image based registration, assist brain shift compensation, and provides interventional decision support…

eess.IV2018

Initialize globally before acting locally: Enabling Landmark-free 3D US to MRI Registration

Julia Rackerseder, Maximilian Baust, Rüdiger Göbl +2

Registration of partial-view 3D US volumes with MRI data is influenced by initialization. The standard of practice is using extrinsic or intrinsic landmarks, which can be very tedi…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.