2 citations · 3 across the 4 of their papers we have counts for
4 papers
Continual atlas-based segmentation of prostate MRI
Amin Ranem, Camila González, Daniel Pinto dos Santos +3
Continual learning (CL) methods designed for natural image classification often fail to reach basic quality standards for medical image segmentation. Atlas-based segmentation, a we…
Exploring SAM Ablations for Enhancing Medical Segmentation in Radiology and Pathology
Amin Ranem, Niklas Babendererde, Moritz Fuchs +1
Medical imaging plays a critical role in the diagnosis and treatment planning of various medical conditions, with radiology and pathology heavily reliant on precise image segmentat…
Task-agnostic Continual Hippocampus Segmentation for Smooth Population Shifts
Camila Gonzalez, Amin Ranem, Ahmed Othman +1
Most continual learning methods are validated in settings where task boundaries are clearly defined and task identity information is available during training and testing. We explo…
Quality monitoring of federated Covid-19 lesion segmentation
Camila Gonzalez, Christian Harder, Amin Ranem +5
Federated Learning is the most promising way to train robust Deep Learning models for the segmentation of Covid-19-related findings in chest CTs. By learning in a decentralized fas…