Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 |
| Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers Inc. |
| Seiten | 1344-1347 |
| Seitenumfang | 4 |
| ISBN (elektronisch) | 9781467319591 |
| Publikationsstatus | Veröffentlicht - 31 Juli 2014 |
| Veranstaltung | 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 - Beijing, China Dauer: 29 Apr. 2014 → 2 Mai 2014 |
Publikationsreihe
| Name | Proceedings (International Symposium on Biomedical Imaging) |
|---|---|
| ISSN (Print) | 1945-7928 |
Abstract
In this contribution, a new algorithm to estimate the cell count from an intensity image of Baby Hamster Kidney (BHK) cells captured by an in-situ microscope is proposed. Given that the local intensity maxima inside a cell share similar location and intensity values, it is proposed to find all the intensity maxima inside each cell cluster present in the image, and then group those who share similar location and intensity values. The total number of cells present in an image is estimated as the sum of the number of groups found in each cluster. The experimental results show that the average cell count improved by 79%, and that the average image processing time improved by 42%.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Biomedizintechnik
- Medizin (insg.)
- Radiologie, Nuklearmedizin und Bildgebung
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- BibTex
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2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014. Institute of Electrical and Electronics Engineers Inc., 2014. S. 1344-1347 ( Proceedings (International Symposium on Biomedical Imaging)).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Cell counting based on local intensity maxima grouping for in-situ microscopy
AU - Rojas, L. D.
AU - Martinez, G.
AU - Scheper, T.
PY - 2014/7/31
Y1 - 2014/7/31
N2 - In this contribution, a new algorithm to estimate the cell count from an intensity image of Baby Hamster Kidney (BHK) cells captured by an in-situ microscope is proposed. Given that the local intensity maxima inside a cell share similar location and intensity values, it is proposed to find all the intensity maxima inside each cell cluster present in the image, and then group those who share similar location and intensity values. The total number of cells present in an image is estimated as the sum of the number of groups found in each cluster. The experimental results show that the average cell count improved by 79%, and that the average image processing time improved by 42%.
AB - In this contribution, a new algorithm to estimate the cell count from an intensity image of Baby Hamster Kidney (BHK) cells captured by an in-situ microscope is proposed. Given that the local intensity maxima inside a cell share similar location and intensity values, it is proposed to find all the intensity maxima inside each cell cluster present in the image, and then group those who share similar location and intensity values. The total number of cells present in an image is estimated as the sum of the number of groups found in each cluster. The experimental results show that the average cell count improved by 79%, and that the average image processing time improved by 42%.
KW - Biomedical imaging
KW - Cell cluster segmentation
KW - Cell counting
KW - Cell image analysis
KW - Detection
KW - Grouping
KW - In-situ microscopy
KW - Local intensity maxima
UR - http://www.scopus.com/inward/record.url?scp=84927919900&partnerID=8YFLogxK
U2 - 10.1109/isbi.2014.6868126
DO - 10.1109/isbi.2014.6868126
M3 - Conference contribution
AN - SCOPUS:84927919900
T3 - Proceedings (International Symposium on Biomedical Imaging)
SP - 1344
EP - 1347
BT - 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
Y2 - 29 April 2014 through 2 May 2014
ER -