1 code implementation • 20 Nov 2023 • Georg Wölflein, Dyke Ferber, Asier Rabasco Meneghetti, Omar S. M. El Nahhas, Daniel Truhn, Zunamys I. Carrero, David J. Harrison, Ognjen Arandjelović, Jakob N. Kather
We question this belief in the context of weakly supervised whole slide image classification, motivated by the emergence of powerful feature extractors trained using self-supervised learning on diverse pathology datasets.
no code implementations • 5 Jun 2023 • Achim Hekler, Roman C. Maron, Sarah Haggenmüller, Max Schmitt, Christoph Wies, Jochen S. Utikal, Friedegund Meier, Sarah Hobelsberger, Frank F. Gellrich, Mildred Sergon, Axel Hauschild, Lars E. French, Lucie Heinzerling, Justin G. Schlager, Kamran Ghoreschi, Max Schlaak, Franz J. Hilke, Gabriela Poch, Sören Korsing, Carola Berking, Markus V. Heppt, Michael Erdmann, Sebastian Haferkamp, Konstantin Drexler, Dirk Schadendorf, Wiebke Sondermann, Matthias Goebeler, Bastian Schilling, Jakob N. Kather, Eva Krieghoff-Henning, Titus J. Brinker
Classifier performance was measured using area under the receiver operating characteristic curve (AUROC), expected calibration error (ECE) and maximum confidence change (MCC) for (I) a single-view scenario, (II) a multiview scenario using multiple artificially modified images per lesion and (III) a multiview scenario with multiple real-world images per lesion.
1 code implementation • 20 Jun 2022 • Adrian Galdran, Katherine J. Hewitt, Narmin L. Ghaffari, Jakob N. Kather, Gustavo Carneiro, Miguel A. González Ballester
In test time, we measure model confidence in predicting this transform, which we expect to be lower for images in the Open Set.