ShaRPy: Shape Reconstruction and Hand Pose Estimation from RGB-D with Uncertainty

no code implementations • 17 Mar 2023 • Vanessa Wirth, Anna-Maria Liphardt, Birte Coppers, Johanna Bräunig, Simon Heinrich, Sigrid Leyendecker, Arnd Kleyer, Georg Schett, Martin Vossiek, Bernhard Egger, Marc Stamminger

Therefore, we propose ShaRPy, the first RGB-D Shape Reconstruction and hand Pose tracking system, which provides uncertainty estimates of the computed pose, e. g., when a finger is hidden or its estimate is inconsistent with the observations in the input, to guide clinical decision-making.

Decision Making Gesture Recognition +3

Advanced neural networks for classification of MRI in psoriatic arthritis, seronegative, and seropositive rheumatoid arthritis

no code implementations • Rheumatology (Oxford) 2022 • Lukas Folle, Sara Bayat, Arnd Kleyer, Filippo Fagni, Lorenz A Kapsner, Maja Schlereth, Timo Meinderink, Katharina Breininger, Koray Tacilar, Gerhard Krönke, Michael Uder, Michael Sticherling, Sebastian Bickelhaupt, Georg Schett, Andreas Maier, Frank Roemer, David Simon

AUROC was 75% for seropositive RA vs. PsA, 74% for seronegative RA vs. PsA and 67% for seropositive vs. seronegative RA.

Deep Learning-Based Classification of Inflammatory Arthritis by Identification of Joint Shape Patterns—How Neural Networks Can Tell Us Where to “Deep Dive” Clinically

no code implementations • Frontiers in Medicine 2022 • Lukas Folle, David Simon, Koray Tascilar, Gerhard Krönke, Anna-Maria Liphardt, Andreas Maier, Georg Schett, Arnd Kleyer

Methods: We trained a novel neural network on 3D articular bone shapes of hand joints of RA and PsA patients as well as HC.

Towards Super-Resolution CEST MRI for Visualization of Small Structures

1 code implementation • 3 Dec 2021 • Lukas Folle, Katharian Tkotz, Fasil Gadjimuradov, Lorenz Kapsner, Moritz Fabian, Sebastian Bickelhaupt, David Simon, Arnd Kleyer, Gerhard Krönke, Moritz Zaiß, Armin Nagel, Andreas Maier

This work paves the way for the prospective investigation of neural networks for super-resolution CEST MRI and, followingly, might lead to a earlier detection of the onset of rheumatic diseases.

Anatomy SSIM +1

Deep learning methods allow fully automated segmentation of metacarpal bones to quantify volumetric bone mineral density

1 code implementation • 6 May 2021 • Lukas Folle, Timo Meinderink, David Simon, Anna-Maria Liphardt, Gerhard Krönke, Georg Schett, Arnd Kleyer, Andreas Maier

Based on a dataset of HR-pQCT volumes with MC measurements for 541 patients with arthritis, a segmentation network is trained.

3D Instance Segmentation