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Ryabchykov, Oleg ; Ramoji, Anuradha ; Bocklitz, Thomas ; Förster, Martin ; Hagel, Stefan ; Kroegel, Claus ; Bauer, Michael ; Neugebauer, Ute ; Popp, Jürgen:
Leukocyte subtypes classification by means of image processing.
In:
Proceedings of the 2016 Federated Conference on Computer Science and Information Systems. -
Piscataway, NJ
: IEEE
,
2016
. - S. 309-316
Abstract
The classification of leukocyte subtypes is a routine method to diagnose many diseases, infections, and inflammations. By applying an automated cell counting procedure, it is possible to decrease analysis time and increase the number of analyzed cells per patient, thereby making the analysis more robust. Here we propose a method, which automatically differentiate between two white blood cell subtypes, which are present in blood in the highest fractions. We apply generalized pseudo-Zernike moments to transfer morphological information of the cells to features and subsequently to a classification model. The first results indicate that information from the morphology can be used to obtain efficient automatic classification, which was demonstrated for the leukocyte subtype classification of neutrophils and lymphocytes. The approach can be extended to other imaging modalities, like different types of staining, spectroscopic techniques, dark field or phase contrast microscopy.
Weitere Angaben
| Publikationsform: | Aufsatz in einem Buch |
|---|---|
| Begutachteter Beitrag: | Ja |
| Keywords: | diseases; image classification; medical image processing; spectroscopy; automated cell counting procedure; dark field; diseases; image processing; imaging modalities; infections; inflammations; leukocyte subtypes classification; lymphocytes; morphological information; neutrophils; phase contrast microscopy; pseudo-Zernike moments; spectroscopic techniques; white blood cell subtypes; Blood; Hospitals; Image color analysis; Manuals; Microscopy; Morphology |
| Institutionen der Universität: | Fakultäten > Fakultät für Mathematik, Physik und Informatik > Institut für Informatik > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie - Univ.-Prof. Dr. Thomas Wilhelm Bocklitz |
| Titel an der UBT entstanden: | Nein |
| Themengebiete aus DDC: | 500 Naturwissenschaften und Mathematik > 530 Physik |
| Eingestellt am: | 15 Mai 2023 11:46 |
| Letzte Änderung: | 15 Mai 2023 11:46 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/76365 |