at Google ScholarTitle data
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
. - pp. 309-316
Abstract in another language
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.
Further data
| Item Type: | Article in a book |
|---|---|
| Refereed: | Yes |
| 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 |
| Institutions of the University: | Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie - Univ.-Prof. Dr. Thomas Wilhelm Bocklitz |
| Result of work at the UBT: | No |
| DDC Subjects: | 500 Science > 530 Physics |
| Date Deposited: | 15 May 2023 11:46 |
| Last Modified: | 15 May 2023 11:46 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/76365 |