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researcher

Marc Huppertz

3 papers here

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

author position
  • middle author2

Across the 2 of 3 papers where every author was matched, so the position is known.

fields
  • physics.med-ph2
  • cs.CV1
ORCID 0009-0004-2801-3679

identity via Semantic Scholar / OpenAlex

most citedReconstruction of Patient-Specific Confounders in AI-based Radiologic Image Interpretation using Generative Pretraining

1 citations · 1 across the 3 of their papers we have counts for

collaborators

3 papers

physics.med-ph2023

Time-efficient combined morphologic and quantitative joint MRI based on clinical image contrasts -- An exploratory in-situ study of standardized cartilage defects

Teresa Lemainque, Nicola Pridöhl, Shuo Zhang +8

OBJECTIVES: Quantitative MRI techniques such as T2 and T1ρ mapping are beneficial in evaluating cartilage and meniscus. We aimed to evaluate the MIXTURE (Multi-Interleaved X-prep…

physics.med-ph2023

Two for One -- Combined Morphologic and Quantitative Knee Joint MRI Using a Versatile Turbo Spin-Echo Platform

Teresa Lemainque, Nicola Pridoehl, Marc Huppertz +9

Introduction: Quantitative MRI techniques such as T2 and T1\r{ho} mapping are beneficial in evaluating knee joint pathologies; however, long acquisition times limit their clinical…

cs.CV2023★ 1 cited

Reconstruction of Patient-Specific Confounders in AI-based Radiologic Image Interpretation using Generative Pretraining

Tianyu Han, Laura Žigutytė, Luisa Huck +9

Detecting misleading patterns in automated diagnostic assistance systems, such as those powered by Artificial Intelligence, is critical to ensuring their reliability, particularly…

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