Publications (15)
Generalizability vs. Robustness: Adversarial Examples for Medical Imaging
Magdalini Paschali, Sailesh Conjeti, Fernando Navarro +1
In this paper, for the first time, we propose an evaluation method for deep learning models that assesses the performance of a model not only in an unseen test scenario, but also i…
Grading Loss: A Fracture Grade-based Metric Loss for Vertebral Fracture Detection
Malek Husseini, Anjany Sekuboyina, Maximilian Loeffler +3
Osteoporotic vertebral fractures have a severe impact on patients' overall well-being but are severely under-diagnosed. These fractures present themselves at various levels of seve…
Deep Reinforcement Learning for Organ Localization in CT
Fernando Navarro, Anjany Sekuboyina, Diana Waldmannstetter +3
Robust localization of organs in computed tomography scans is a constant pre-processing requirement for organ-specific image retrieval, radiotherapy planning, and interventional im…
A Deep Learning Approach to Predicting Collateral Flow in Stroke Patients Using Radiomic Features from Perfusion Images
Giles Tetteh, Fernando Navarro, Johannes Paetzold +3
Collateral circulation results from specialized anastomotic channels which are capable of providing oxygenated blood to regions with compromised blood flow caused by ischemic injur…
Focused Decoding Enables 3D Anatomical Detection by Transformers
Bastian Wittmann, Fernando Navarro, Suprosanna Shit +1
Detection Transformers represent end-to-end object detection approaches based on a Transformer encoder-decoder architecture, exploiting the attention mechanism for global relation…
CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography
Murong Xu, Tamaz Amiranashvili, Fernando Navarro +30
Accurate delineation of anatomical structures in volumetric CT scans is crucial for diagnosis and treatment planning. While AI has advanced automated segmentation, current approach…