Scanning probe microscopy with landmark referenced control for direct biological investigations.
We report the successful use of continuous wavelet transforms applied to atomic force microscope data sets for landmark recognition of biological features. The data sets were images of mixed red and white blood cells. Contrast enhancement followed by continuous wavelet transform of the data was used to successfully distinguish erythrocytes from neutrophil and monocyte leukocytes within the mixed cell images. All of the above are spherical objects between 6 and 8 microns in diameter, which demonstrates the ability to sort similar biological objects into distinct classes. The implications for development of on-line scanning probe recognition microscopy are discussed.
Goolsby
B
B
Department of Electrical and Computer Engineering, Michigan State University, East Lansing, Michigan 48824, USA.
Chen
Q
Q
Udpa
L
L
Fan
Y
Y
Samona
R
R
Bhooravan
B
B
Salam
F M
FM
Wang
D H
DH
Ayres
V M
VM
D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D002465:Cell Movement / Q000502:physiology; D002478:Cells, Cultured; D018920:Coculture Techniques; D004912:Erythrocytes / Q000145:classification / Q000502:physiology / Q000648:ultrastructure*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007962:Leukocytes / Q000145:classification / Q000502:physiology / Q000648:ultrastructure*; D008297:Male; D018625:Microscopy, Atomic Force / Q000379:methods; D020527:Microscopy, Scanning Probe / Q000379:methods*; D010363:Pattern Recognition, Automated; D051381:Rats; D017208:Rats, Wistar