University of Heidelberg
Faculty of Medicine Mannheim
University Hospital Mannheim
CKM receives DFG funding for Project "Prdiktion von Therapieansprechen und Outcome beim lokal fortgeschrittenen Rektum-Karzinom mittels Radiomics und Deep Learning: eine beispielhafte Anwendung fr eine allgemein verwendbare, Deep Learning basierte Prozessierungs-Pipeline fr die Bild-Klassifikation" read more.
Alena-Kathrin Schnurr presented on our research on AI in medical imaging @ Research Plus forum
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Dr. Mathias Davids wins the I. I. Rabi Award of the International Society for Magnetic Resonance in Medicine (ISMRM),
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{C}lassification of {S}egmented {R}egions in {B}rightfield {M}icroscope {I}mages

M. Tscherepanow, F. Zöllner and F. Kummert

Proceedings of the International Conference on Pattern Recognition (ICPR), 3, pp.972-975

The subcellular localisation of proteins in living cells is an important step to determine their function. A common method is the evaluation of fluorescence images. The position of marked proteins, visible as bright spots, enables conclusions concerning their function. In order to determine the subcellular localisation, it is crucial to know the exact positions of the considered cells within an image. These are provided by the segmentation of a corresponding brightfield microscope image. As the resulting segments do not exclusively comprise cells, they have to be classified. Therefore, we propose an approach for the classification of the resulting segments in `cells' and `non-cells', which is an essential step of the automatic recognition of cells and thus of the automatic subcellular localisation of proteins in living cells.

Contact: Prof. Dr. Frank Zöllner last modified: 21.09.2020
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