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Michael Rebsamen

4 papers hereh-index 12552 citations31 works total

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

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • eess.IV2
  • cs.CV1
  • cs.LG1

identity via Semantic Scholar / OpenAlex

activity
20182021
most citedQU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results

58 citations · 65 across the 4 of their papers we have counts for

collaborators
Showing eess.IVShow all

2 papers · 1 filter

eess.IV2021★ 58 cited

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results

Raghav Mehta, Angelos Filos, Ujjwal Baid +89

Deep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges.…

eess.IV2019

Stratify or Inject: Two Simple Training Strategies to Improve Brain Tumor Segmentation

Raphael Meier, Michael Rebsamen, Urspeter Knecht +3

Deep learning methods for brain tumor segmentation are typically trained in an ad hoc fashion on all available data. Brain tumors are tremendously heterogeneous in image appearance…

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