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Humboldt-Universität zu Berlin - Mathematisch-Naturwissenschaftliche Fakultät - Institut für Informatik

Institutskolloquium: Frau Dr. Dagmar Kainmüller

Wann 12.02.2020 ab 09:15 (Europe/Berlin / UTC100) iCal
Wo Rudower Chaussee 25, Humboldt-Kabinett

Am Mittwoch, den 12.2.2020, wird um 9.00 Uhr c.t. Frau Dr. Dagmar Kainmüller, Nachwuchsgruppenleitein am MDC, im HUK einen Vortrag zum Thema

    Learning Instance Segmentation in Biomedical Image Data


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Instance segmentation is the task of separately delineating each object in an image. It has a wide range of applications in natural images as well as in the biomedical domain, where there is, e.g., a pervasive need to delineate each cell of a biological sample in microscopy images. In this talk I will present our new method for instance segmentation, termed PatchPerPix, that outperforms the state of the art on benchmark microscopy data. Furthermore, I will discuss the related task of semantic parts segmentation, where instances are not just delineated, but also assigned individual semantic labels. I will present our efforts towards unsupervised semantic parts segmentation on the example of the worm C. elegans, a popular model organism that is stereotypically composed of a fixed number of cells of which each one has a unique biological name.