TY - GEN
T1 - Cell identification with computational
T2 - 3-D holographic microscopy
AU - Moon, Inkyu
AU - Daneshpanah, Mehdi
AU - Anand, Arun
AU - Javidi, Bahram
PY - 2011/6
Y1 - 2011/6
N2 - Techniques in 3-D digital holographic microscopy (DHM) integrated with numerical processing are enabling researchers to obtain rich, quantitative information about the structure of cells and microorganisms in noninvasive real-time conditions. In single-exposure DHM, a digital Fresnel hologram is recorded from the specimen in either on-axis or off-axis configurations. The microscope objective that is used for magnifying the field can be removed in a lensless implementation. One can reconstruct the specimen's 3-D image, or a stack of 2-D images, from the recorded digital hologram by inverse Fresnel transformation. Cross-comparison with 2-D intensity images has shown that complex 3-D images that are reconstructed from digital holograms provide more discriminating features and allow for better classification of cells. The 3-D reconstruction of cells can be used with statistical pattern recognition algorithms to recognize and classify the cells in real-time.
AB - Techniques in 3-D digital holographic microscopy (DHM) integrated with numerical processing are enabling researchers to obtain rich, quantitative information about the structure of cells and microorganisms in noninvasive real-time conditions. In single-exposure DHM, a digital Fresnel hologram is recorded from the specimen in either on-axis or off-axis configurations. The microscope objective that is used for magnifying the field can be removed in a lensless implementation. One can reconstruct the specimen's 3-D image, or a stack of 2-D images, from the recorded digital hologram by inverse Fresnel transformation. Cross-comparison with 2-D intensity images has shown that complex 3-D images that are reconstructed from digital holograms provide more discriminating features and allow for better classification of cells. The 3-D reconstruction of cells can be used with statistical pattern recognition algorithms to recognize and classify the cells in real-time.
UR - http://www.scopus.com/inward/record.url?scp=79960227656&partnerID=8YFLogxK
U2 - 10.1364/OPN.22.6.000018
DO - 10.1364/OPN.22.6.000018
M3 - Article
AN - SCOPUS:79960227656
SN - 1047-6938
VL - 22
SP - 18
EP - 23
JO - Optics and Photonics News
JF - Optics and Photonics News
ER -