1 code implementation • 31 Jul 2020 • Amelia Jiménez-Sánchez, Diana Mateus, Sonja Kirchhoff, Chlodwig Kirchhoff, Peter Biberthaler, Nassir Navab, Miguel A. González Ballester, Gemma Piella
In this paper, we propose a method for the automatic classification of proximal femur fractures into 3 and 7 AO classes based on a Convolutional Neural Network (CNN).
no code implementations • 1 Apr 2020 • Amelia Jiménez-Sánchez, Diana Mateus, Sonja Kirchhoff, Chlodwig Kirchhoff, Peter Biberthaler, Nassir Navab, Miguel A. González Ballester, Gemma Piella
Current deep-learning based methods do not easily integrate to clinical protocols, neither take full advantage of medical knowledge.
no code implementations • 4 Feb 2019 • Amelia Jiménez-Sánchez, Anees Kazi, Shadi Albarqouni, Chlodwig Kirchhoff, Peter Biberthaler, Nassir Navab, Sonja Kirchhoff, Diana Mateus
We demonstrate the feasibility of a fully automatic computer-aided diagnosis (CAD) tool, based on deep learning, that localizes and classifies proximal femur fractures on X-ray images according to the AO classification.
no code implementations • 27 Sep 2018 • Amelia Jiménez-Sánchez, Anees Kazi, Shadi Albarqouni, Sonja Kirchhoff, Alexandra Sträter, Peter Biberthaler, Diana Mateus, Nassir Navab
In this paper, we target the problem of fracture classification from clinical X-Ray images towards an automated Computer Aided Diagnosis (CAD) system.