Výsledky vyhledávání - "Berger Alexander"

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Topograph: An efficient Graph-Based Framework for Strictly Topology Preserving Image Segmentation

Autor: Lux, Laurin, Berger, Alexander H., Weers, Alexander, Stucki, Nico, Rueckert, Daniel, Bauer, Ulrich, Paetzold, Johannes C.

Topological correctness plays a critical role in many image segmentation tasks, yet most networks are trained using pixel-wise loss functions, such as Dice, neglecting topological accuracy. Existing topology-aware methods often lack robust topologica

Externí odkaz: http://arxiv.org/abs/2411.03228

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Topologically Faithful Multi-class Segmentation in Medical Images

Autor: Berger, Alexander H., Stucki, Nico, Lux, Laurin, Buergin, Vincent, Shit, Suprosanna, Banaszak, Anna, Rueckert, Daniel, Bauer, Ulrich, Paetzold, Johannes C.

Publikováno v: MICCAI 2024, Lecture Notes in Computer Science, vol. 15008, pp. 721-731, 2024

Topological accuracy in medical image segmentation is a highly important property for downstream applications such as network analysis and flow modeling in vessels or cell counting. Recently, significant methodological advancements have brought well-

Externí odkaz: http://arxiv.org/abs/2403.11001

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Cross-domain and Cross-dimension Learning for Image-to-Graph Transformers

Autor: Berger, Alexander H., Lux, Laurin, Shit, Suprosanna, Ezhov, Ivan, Kaissis, Georgios, Menten, Martin J., Rueckert, Daniel, Paetzold, Johannes C.

Direct image-to-graph transformation is a challenging task that solves object detection and relationship prediction in a single model. Due to the complexity of this task, large training datasets are rare in many domains, which makes the training of l

Externí odkaz: http://arxiv.org/abs/2403.06601

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