Unsupervised cell identification on multidimensional X-ray fluorescence datasets
A novel approach to locate, identify and refine positions and whole areas of cell structures based on elemental contents measured by X-ray fluorescence microscopy is introduced. It is shown that, by initializing with only a handful of prototypical cell regions, this approach can obtain consistent id...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | Journal of synchrotron radiation. - 1994. - 21(2014), Pt 3 vom: 01. Mai, Seite 568-79
|
|---|
| 1. Verfasser: |
Wang, Siwei
(VerfasserIn) |
|---|
| Weitere Verfasser: |
Ward, Jesse,
Leyffer, Sven,
Wild, Stefan M,
Jacobsen, Chris,
Vogt, Stefan |
|---|
| Format: | Online-Aufsatz
|
|---|
| Sprache: | English |
|---|
| Veröffentlicht: |
2014
|
|---|
| Zugriff auf das übergeordnete Werk: | Journal of synchrotron radiation
|
|---|
| Schlagworte: | Journal Article
Research Support, U.S. Gov't, Non-P.H.S.
X-ray fluorescence microscopy (XFM)
cell identification
modeling overlapping cells
trace element distributions
unsupervised object recognition |
|---|