Search Results for author: Hartmut Häntze

Found 3 papers, 2 papers with code

Incorporating Anatomical Awareness for Enhanced Generalizability and Progression Prediction in Deep Learning-Based Radiographic Sacroiliitis Detection

1 code implementation • 12 May 2024 • Felix J. Dorfner, Janis L. Vahldiek, Leonhard Donle, Andrei Zhukov, Lina Xu, Hartmut Häntze, Marcus R. Makowski, Hugo J. W. L. Aerts, Fabian Proft, Valeria Rios Rodriguez, Judith Rademacher, Mikhail Protopopov, Hildrun Haibel, Torsten Diekhoff, Murat Torgutalp, Lisa C. Adams, Denis Poddubnyy, Keno K. Bressem

For the second cohort, follow-up data of 311 patients was used to examine progression prediction capabilities.

Anatomy Specificity

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MRSegmentator: Robust Multi-Modality Segmentation of 40 Classes in MRI and CT Sequences

1 code implementation • 10 May 2024 • Hartmut Häntze, Lina Xu, Felix J. Dorfner, Leonhard Donle, Daniel Truhn, Hugo Aerts, Mathias Prokop, Bram van Ginneken, Alessa Hering, Lisa C. Adams, Keno K. Bressem

Results: The model showcased high accuracy in segmenting well-defined organs, achieving Dice Similarity Coefficient (DSC) scores of 0. 97 for the right and left lungs, and 0. 95 for the heart.

Model Optimization Organ Segmentation +2

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Improve Cross-Modality Segmentation by Treating MRI Images as Inverted CT Scans

no code implementations • 4 May 2024 • Hartmut Häntze, Lina Xu, Leonhard Donle, Felix J. Dorfner, Alessa Hering, Lisa C. Adams, Keno K. Bressem

Computed tomography (CT) segmentation models frequently include classes that are not currently supported by magnetic resonance imaging (MRI) segmentation models.

Computed Tomography (CT) MRI segmentation +1

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