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of 89 925
pro vyhledávání: '"Hein, Than"'
Autor:
Kahl, Kim-Celine, Erkan, Selen, Traub, Jeremias, Lüth, Carsten T., Maier-Hein, Klaus, Maier-Hein, Lena, Jaeger, Paul F.
Vision-Language Models (VLMs) have great potential in medical tasks, like Visual Question Answering (VQA), where they could act as interactive assistants for both patients and clinicians. Yet their robustness to distribution shifts on unseen data rem
Externí odkaz:
http://arxiv.org/abs/2411.19688
Autor:
Fischer, Maximilian, Hauptmann, Florian M., Peretzke, Robin, Naser, Paul, Neher, Peter, Neumann, Jan-Oliver, Maier-Hein, Klaus
Although advances in brain surgery techniques have led to fewer postoperative complications requiring Intensive Care Unit (ICU) monitoring, the routine transfer of patients to the ICU remains the clinical standard, despite its high cost. Predictive G
Externí odkaz:
http://arxiv.org/abs/2412.15818
Autor:
Fischer, Maximilian, Neher, Peter, Schüffler, Peter, Ziegler, Sebastian, Xiao, Shuhan, Peretzke, Robin, Clunie, David, Ulrich, Constantin, Baumgartner, Michael, Muckenhuber, Alexander, Almeida, Silvia Dias, Götz, Michael, Kleesiek, Jens, Nolden, Marco, Braren, Rickmer, Maier-Hein, Klaus
Digital pathology offers a groundbreaking opportunity to transform clinical practice in histopathological image analysis, yet faces a significant hurdle: the substantial file sizes of pathological Whole Slide Images (WSI). While current digital patho
Externí odkaz:
http://arxiv.org/abs/2412.13137
Dense prediction tasks such as object detection and segmentation require high-quality labels at pixel level, which are costly to obtain. Recent advances in foundation models have enabled the generation of autolabels, which we find to be competitive b
Externí odkaz:
http://arxiv.org/abs/2412.10032
The field of medical imaging AI is currently undergoing rapid transformations, with methodical research increasingly translated into clinical practice. Despite these successes, research suffers from knowledge silos, hindering collaboration and progre
Externí odkaz:
http://arxiv.org/abs/2412.08763
Autor:
Yin, Xiaoyu, Peri, Elisabetta, Pelssers, Eduard, Toonder, Jaap den, Klous, Lisa, Daanen, Hein, Mischi, Massimo
Background and objective: Diabetes is one of the four leading causes of death worldwide, necessitating daily blood glucose monitoring. While sweat offers a promising non-invasive alternative for glucose monitoring, its application remains limited due
Externí odkaz:
http://arxiv.org/abs/2412.02870
Vision-Language models like CLIP have been shown to be highly effective at linking visual perception and natural language understanding, enabling sophisticated image-text capabilities, including strong retrieval and zero-shot classification performan
Externí odkaz:
http://arxiv.org/abs/2412.00727
Autor:
Isensee, Fabian, Kirchhoff, Yannick, Kraemer, Lars, Rokuss, Maximilian, Ulrich, Constantin, Maier-Hein, Klaus H.
This paper presents our approach to scaling the nnU-Net framework for multi-structure segmentation on Cone Beam Computed Tomography (CBCT) images, specifically in the scope of the ToothFairy2 Challenge. We leveraged the nnU-Net ResEnc L model, introd
Externí odkaz:
http://arxiv.org/abs/2411.17213
In multi-state models based on high-dimensional data, effective modeling strategies are required to determine an optimal, ideally parsimonious model. In particular, linking covariate effects across transitions is needed to conduct joint variable sele
Externí odkaz:
http://arxiv.org/abs/2411.17394
This paper presents ETA-IK, a novel Execution-Time-Aware Inverse Kinematics method tailored for dual-arm robotic systems. The primary goal is to optimize motion execution time by leveraging the redundancy of both arms, specifically in tasks where onl
Externí odkaz:
http://arxiv.org/abs/2411.14381