Enhancing Interpretability of Vertebrae Fracture Grading using Human-interpretable Prototypes

no code implementations • 3 Apr 2024 • Poulami Sinhamahapatra, Suprosanna Shit, Anjany Sekuboyina, Malek Husseini, David Schinz, Nicolas Lenhart, Joern Menze, Jan Kirschke, Karsten Roscher, Stephan Guennemann

In this work, we propose a novel interpretable-by-design method, ProtoVerse, to find relevant sub-parts of vertebral fractures (prototypes) that reliably explain the model's decision in a human-understandable way.

Medical Diagnosis

Grading Loss: A Fracture Grade-based Metric Loss for Vertebral Fracture Detection

no code implementations • 18 Aug 2020 • Malek Husseini, Anjany Sekuboyina, Maximilian Loeffler, Fernando Navarro, Bjoern H. Menze, Jan S. Kirschke

Building on state-of-art metric losses, we present a novel Grading Loss for learning representations that respect Genant's fracture grading scheme.

General Classification Representation Learning