Titlebook: Bildverarbeitung für die Medizin 2024; Proceedings, German Andreas Maier,Thomas M. Deserno,Thomas Tolxdorff Conference proceedings 2024 De

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Privacy-enhancing Image Sampling for the Synthesis of High-quality Anonymous Chest Radiographs, chest X-ray datasets. However, the presence of patient-specific biometric information in chest radiographs impedes direct and public sharing of such data for research purposes due to the potential risk of patient re-identification. In this context, synthetic data generation emerges as a solution fo

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Displacement Representation for Conditional Point Cloud Registration,ps. Applications include outpatient follow-up assessments and intraoperative scenarios like ultrasound-guided navigation. Through a simple modification in displacement prediction representation, we enhance registration results by more than 25% w.r.t. prior work while preserving the model-free paradi

MUMP

Joint Learning of Image Registration and Change Detection for Lung CT Images,ncy in diagnostic reading, but also to decrease the number of missed abnormalities. Classically, change maps are created from difference images after an image registration step, which requires a careful balance in order to neither generate artifacts nor disguise relevant changes.We propose jointly l

Engulf

Abstract: Focused Unsupervised Image Registration for Structure-specific Population Analysis,ies on a single structure or image region in order to identify variations to discriminate between patient groups. In many applications, existing automatic segmentation tools or trained neural networks are used to identify relevant image structures. However, if new structures are to be analyzed, thes

激怒

Abstract: Combined 3D Dataset for CT- and Point Cloud-based Intra-patient Lung Registration Lung250PD, estimation of tumour motion in radiotherapy planning or tracking of lung nodules.With recent developments, deep learning-based methods are competing for state-of-the-art in various image registration tasks. Additionally, geometric deep learning on point clouds – in particular learning-based poin