6 papers · 1 filter
Subtraction-Based Tumor Segmentation and Lesion-Centered pCR Prediction for the MAMA-MIA Challenge
Kai Geissler, Raphael Schäfer
We describe the submission of team FME to the MAMA-MIA Challenge, which evaluated primary tumor segmentation and prediction of pathological complete response (pCR) from pretreatmen…
CoMeT: A foundation model for medical image analysis through federated, multidimensional context integration
J. Raphael Schäfer, Kai Geissler, Till Nicke +27
Medical foundation models improve generalization when training AI models with limited labeled data, but remain confined to a single specialty, such as pathology or radiology, and t…
RadYOLO: Computationally Efficient 3D Object Detection and Segmentation in CT and MRI
Kai Geissler, Laurens Müller-Groh, Hans Meine
Object detection and segmentation in three-dimensional medical images is a very active area of research. However, most proposed deep learning models carry a high computational cost…
The MAMA-MIA Challenge: Advancing Generalizability and Fairness in Breast MRI Tumor Segmentation and Treatment Response Prediction
Lidia Garrucho, Smriti Joshi, Kaisar Kushibar +43
Breast cancer is the most frequently diagnosed malignancy among women worldwide and a leading cause of cancer-related mortality. Dynamic contrast-enhanced magnetic resonance imagin…
Depth to Anatomy: Organ Localization from Depth Images for Automated Patient Table Positioning in Radiology Workflow
Eytan Kats, Kai Geissler, Daniel Mensing +4
In clinical radiology, accurate patient table positioning is essential to align specific internal organs of interest with the scanner imaging isocenter, ensuring image quality and…
Internal Organ Localization Using Depth Images
Eytan Kats, Kai Geißler, Jochen G. Hirsch +2
Automated patient positioning is a crucial step in streamlining MRI workflows and enhancing patient throughput. RGB-D camera-based systems offer a promising approach to automate th…