8 Result(s)
within
Chapter
Tassilo Wald
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Chapter and Conference Paper
Abstract: Multi-dataset Approach to Medical Image Segmentation
The medical imaging community generates a wealth of data-sets, many of which are openly accessible and annotated for specific diseases and tasks such as multi-organ or lesion segmentation. Current practices co...
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Chapter and Conference Paper
Abstract: RecycleNet
Despite the remarkable success of deep learning systems over the last decade, a key difference still remains between neural network and human decision-making: As humans, we can not only form a decision on the ...
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Chapter and Conference Paper
Abstract: Reformulating COPD Classification on Chest CT Scans as Anomaly Detection using Contrastive Representations
Classification of heterogeneous diseases is challenging due to their complexity, variability of symptoms and imaging findings. Chronic obstructive pulmonary disease (COPD) is a prime example, being underdiagno...
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Chapter and Conference Paper
Abstract: Automated Detection and Quantification of Brain Metastases on Clinical MRI Data using CNNs
Reliable detection and precise volumetric quantification of brain metastases (BM) on MRI are essential for guiding treatment decisions. We evaluate the potential of CNNs for automated detection and quantificat...
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Chapter and Conference Paper
Taming Detection Transformers for Medical Object Detection
The accurate detection of suspicious regions in medical images is an error-prone and time-consuming process required by many routinely performed diagnostic procedures. To support clinicians during this difficu...
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Chapter and Conference Paper
Extending nnU-Net Is All You Need
Semantic segmentation is one of the most popular research areas in medical image computing. Perhaps surprisingly, despite its conceptualization dating back to 2018, nnU-Net continues to provide competitive out...
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Chapter and Conference Paper
MultiTalent: A Multi-dataset Approach to Medical Image Segmentation
The medical imaging community generates a wealth of data-sets, many of which are openly accessible and annotated for specific diseases and tasks such as multi-organ or lesion segmentation. Current practices co...
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Chapter and Conference Paper
cOOpD: Reformulating COPD Classification on Chest CT Scans as Anomaly Detection Using Contrastive Representations
Classification of heterogeneous diseases is challenging due to their complexity, variability of symptoms and imaging findings. Chronic Obstructive Pulmonary Disease (COPD) is a prime example, being underdiagno...
