2 Works

Data from: On the objectivity, reliability, and validity of deep learning enabled bioimage analyses

Dennis Segebarth, Matthias Griebel, Nikolai Stein, Cora R. Von Collenberg, Corinna Martin, Dominik Fiedler, Lucas B. Comeras, Anupam Sah, Victoria Schoeffler, Theresa Lüffe, Alexander Dürr, Rohini Gupta, Manju Sasi, Christina Lillesaar, Maren D. Lange, Ramon O. Tasan, Nicolas Singewald, Hans-Christian Pape, Christoph M. Flath & Robert Blum
Bioimage analysis of fluorescent labels is widely used in the life sciences. Recent advances in deep learning (DL) allow automating time-consuming manual image analysis processes based on annotated training data. However, manual annotation of fluorescent features with a low signal-to-noise ratio is somewhat subjective. Training DL models on subjective annotations may be instable or yield biased models. In turn, these models may be unable to reliably detect biological effects. An analysis pipeline integrating data annotation,...

Extracellular matrix protein signature of recurrent spontaneous cervical artery dissection

Lukas Mayer, Raimund Pechlaner, Javier Barallobre-Barreiro, Christian Boehme, Thomas Toell, Marc Lynch, Xiaoke Yin, Johann Willeit, Elke Ruth Gizewski, Paul Perco, Gudrun Ratzinger, Stefan Kiechl, Manuel Mayr & Michael Knoflach
Objective To assess whether connective tissue disorder is evident in patients with spontaneous cervical artery dissection and therefore identify patients at risk of recurrence using a cutting-edge quantitative proteomics approach. Methods In the ReSect-study all patients with spontaneous cervical artery dissection treated at the Innsbruck University Hospital since 1996 were invited to attend a standardized clinical follow-up examination. Protein abundance in skin punch biopsies (n=50) was evaluated by a cutting-edge quantitative proteomics approach (liquid chromatography-mass...

Registration Year

  • 2020

Resource Types

  • Dataset


  • Innsbruck Medical University
  • University of Würzburg
  • University of Münster
  • University Hospital Würzburg
  • University of Innsbruck