Biomedical Engineering Reference
In-Depth Information
Figure 8.2D
were automatically matched to the orientations of their corresponding heads for
quantifying healthy sperm. Through this orientation screening process, round cells or
unhealthy sperm were rejected because they lacked matching tails or had unusual curvature
on their tails (see
Figure 8.2D
). These automatic detection results were also validated with a
regular microscope image taken on the same FOV, as shown in
Figure 8.2E
.
As an example of motile sperm quantification with our partially coherent lensless
holography platform,
Figures 8.3 and 8.4
show differential imaging and automated tracking
results from a typical semen sample. Digital subtraction of consecutive lensfree frames took
away all the stationary holograms and kept only the differential holograms of the motile
sperm, as described in
Section 8.4
and illustrated in
Figure 8.3A
. These differential
holograms preserved the information about each motile sperm's displacement between these
two consecutive frames, including its magnitude and direction. The holographic
reconstruction on these differential holograms revealed two spots for each motile sperm:
one dark spot indicating its start position and another bright one for its end position (see
Figure 8.3B
). Based on these reconstructed differential images, the dynamic trajectories of
the motile sperm were quantified over the entire imaging FOV (
B
24 mm
2
) as illustrated in
Figure 8.4A
. To determine the speed distribution of these sperm shown in
Figure 8.4A
, the
displacements of individual motile sperm were linked across all the 20 lensless frames
acquired within
B
10 s and their time-averaged speed distribution was plotted out as a speed
histogram as shown in
Figure 8.4B
. This average speed histogram provided by our lensfree
imaging platform is essentially equivalent to the distribution of sperm straight-line velocity
(also known as VSL) reported by commercial CASA systems. Since VSL has been reported
to highly correlate with the success rate of in vitro fertilization
[43]
, the average sperm
speed provided by this platform should also be an effective indicator for male fertility.
Finally, the automated counting accuracy of this on-chip imaging platform should also be
validated by comparing its results against manual counting results obtained with an optical
microscope, which is still considered as one of the gold standards for semen analysis.
Figure 8.5
compares the automatic counting results achieved with our lensless holographic
microscope against the manual counting results provided with a conventional bright-field
microscope. These two sets of results are based on the same 12 semen samples containing
both immotile and motile sperm at various concentration levels. The results of this
comparison verified that our automated on-chip semen analysis platform can accurately
quantify a sperm density up to
B
12 million sperm per ml. Such a large dynamic range
permits this on-chip imaging platform to reliably analyze human semen samples with a
dilution factor of 1
10-fold. Additionally,
Figure 8.5
also points to this platform's superior
ability on automatic analysis of semen samples with very low sperm concentrations. For
example, the lowest concentration in
Figure 8.5B
, that is, 0.09 million sperm per ml, was
defined by 42 sperm tracked by this platform over its 24 mm
2
FOV. With a conventional
microscope equipped with a 20
3
objective lens, one would need to look at almost 100
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