Mesoscopic calcium imaging in a head-unrestrained male non-human primate using a lensless microscope
Nature Communications,
Год журнала:
2024,
Номер
15(1)
Опубликована: Фев. 10, 2024
Mesoscopic
calcium
imaging
enables
studies
of
cell-type
specific
neural
activity
over
large
areas.
A
growing
body
literature
suggests
that
can
be
different
when
animals
are
free
to
move
compared
they
restrained.
Unfortunately,
existing
systems
for
dynamics
areas
in
non-human
primates
(NHPs)
table-top
devices
require
restraint
the
animal's
head.
Here,
we
demonstrate
an
device
capable
mesoscale
a
head-unrestrained
male
primate.
We
successfully
miniaturize
our
system
by
replacing
lenses
with
optical
mask
and
computational
algorithms.
The
resulting
lensless
microscope
fit
comfortably
on
NHP,
allowing
its
head
freely
while
imaging.
able
measure
orientation
columns
maps
20
mm2
field-of-view
macaque.
Our
work
establishes
mesoscopic
using
as
powerful
approach
studying
under
more
naturalistic
conditions.
Язык: Английский
Real-time, deep-learning aided lensless microscope
Biomedical Optics Express,
Год журнала:
2023,
Номер
14(8), С. 4037 - 4037
Опубликована: Июль 4, 2023
Traditional
miniaturized
fluorescence
microscopes
are
critical
tools
for
modern
biology.
Invariably,
they
struggle
to
simultaneously
image
with
a
high
spatial
resolution
and
large
field
of
view
(FOV).
Lensless
offer
solution
this
limitation.
However,
real-time
visualization
samples
is
not
possible
lensless
imaging,
as
reconstruction
can
take
minutes
complete.
This
poses
challenge
usability,
crucial
feature
that
assists
users
in
identifying
locating
the
imaging
target.
The
issue
particularly
pronounced
operate
at
close
distances.
Imaging
distances
requires
shift-varying
deconvolution
account
variation
point
spread
function
(PSF)
across
FOV.
Here,
we
present
microscope
achieves
by
eliminating
use
an
iterative
algorithm.
neural
network-based
method
show
here,
more
than
10000
times
increase
speed
compared
reconstruction.
increased
allows
us
visualize
results
our
25
frames
per
second
(fps),
while
achieving
better
7
µm
over
FOV
10
mm
Язык: Английский
Wide-field, high-resolution reconstruction in computational multi-aperture miniscope using a Fourier neural network
Optica,
Год журнала:
2024,
Номер
11(6), С. 860 - 860
Опубликована: Май 28, 2024
Traditional
fluorescence
microscopy
is
constrained
by
inherent
trade-offs
among
resolution,
field
of
view,
and
system
complexity.
To
navigate
these
challenges,
we
introduce
a
simple
low-cost
computational
multi-aperture
miniature
microscope,
utilizing
microlens
array
for
single-shot
wide-field,
high-resolution
imaging.
Addressing
the
challenges
posed
extensive
view
multiplexing
non-local,
shift-variant
aberrations
in
this
device,
present
SV-FourierNet,
multi-channel
Fourier
neural
network.
SV-FourierNet
facilitates
image
reconstruction
across
entire
imaging
through
its
learned
global
receptive
field.
We
establish
close
relationship
between
physical
spatially
varying
point-spread
functions
network's
effective
This
ensures
that
has
effectively
encapsulated
our
physically
meaningful
function
reconstruction.
Training
conducted
entirely
on
physics-based
simulator.
showcase
video
reconstructions
colonies
freely
moving
C.
elegans
mouse
brain
section.
Our
augmented
with
represents
major
advancement
may
find
broad
applications
biomedical
research
other
fields
requiring
compact
solutions.
Язык: Английский
Advances in Portable Optical Microscopy Using Cloud Technologies and Artificial Intelligence for Medical Applications
Sensors,
Год журнала:
2024,
Номер
24(20), С. 6682 - 6682
Опубликована: Окт. 17, 2024
The
need
for
faster
and
more
accessible
alternatives
to
laboratory
microscopy
is
driving
many
innovations
throughout
the
image
data
acquisition
chain
in
biomedical
field.
Benchtop
microscopes
are
bulky,
lack
communications
capabilities,
require
trained
personnel
analysis.
New
technologies,
such
as
compact
3D-printed
devices
integrated
with
Internet
of
Things
(IoT)
sharing
cloud
computing,
well
automated
processing
using
deep
learning
algorithms,
can
address
these
limitations
enhance
conventional
imaging
workflow.
This
review
reports
on
recent
advancements
microscope
miniaturization,
a
focus
emerging
technologies
photoacoustic
established
approaches
like
smartphone-based
microscopy.
potential
applications
IoT
examined
detail.
Furthermore,
this
discusses
evolution
microscopy,
transitioning
from
traditional
methods
that
facilitate
enhancement
interpretation.
Despite
numerous
field,
there
noticeable
studies
holistically
entire
chain.
aims
highlight
artificial
intelligence
(AI)
combination
portable
emphasizing
importance
comprehensive
approach
chain,
portability
Язык: Английский
Lensless imaging with a programmable Fresnel zone aperture
Science Advances,
Год журнала:
2025,
Номер
11(12)
Опубликована: Март 21, 2025
Optical
imaging
has
long
been
dominated
by
traditional
lens-based
systems
that,
despite
their
success,
are
inherently
limited
size,
weight,
and
cost.
Lensless
seeks
to
overcome
these
limitations
replacing
lenses
with
thinner,
lighter,
cheaper
optical
modulators
reconstructing
images
computationally,
while
facing
trade-offs
in
image
quality,
artifacts,
flexibility
inherent
static
modulation.
Here,
we
propose
a
lensless
method
programmable
Fresnel
zone
aperture
(FZA),
termed
LIP.
With
commercial
liquid
crystal
display,
designed
an
integrated
LIP
module
demonstrated
its
capability
of
high-quality
artifact-free
reconstruction
through
dynamic
modulation
offset-FZA
parallel
merging.
Compared
static-modulation
approaches,
achieves
2.5×
resolution
enhancement
3
decibels
improvement
signal-to-noise
ratio
“static
mode”
maintaining
interaction
frame
rate
15
frames
per
second
“dynamic
mode.”
Experimental
results
demonstrate
LIP’s
potential
as
miniaturized
platform
for
versatile
advanced
tasks
like
virtual
reality
human-computer
interaction.
Язык: Английский
DeepLeMiN: Deep-learning-empowered Physics-aware Lensless Miniscope
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Май 6, 2024
Abstract
Mask-based
lensless
fluorescence
microscopy
is
a
compact,
portable
imaging
technique
promising
for
biomedical
research.
It
forms
images
through
thin
optical
mask
near
the
camera
without
bulky
optics,
enabling
snapshot
three-dimensional
and
scalable
field
of
view
(FOV)
increasing
device
thickness.
Lensless
relies
on
computational
algorithms
to
solve
inverse
problem
object
reconstruction.
However,
there
has
been
lack
efficient
reconstruction
large-scale
data.
Furthermore,
entire
FOV
typically
reconstructed
as
whole,
which
demands
substantial
resources
limits
scalability
FOV.
Here,
we
developed
DeepLeMiN,
microscope
with
custom
designed
multi-stage
physics-informed
deep
learning
model.
This
not
only
enables
localized
FOVs,
but
also
significantly
reduces
resource
facilitates
real-time
Our
algorithm
can
reconstruct
volumes
over
4×6×0.6
mm
3
,
achieving
lateral
axial
resolution
∼10
µm
∼50
respectively.
We
demonstrated
significant
improvement
in
both
quality
speed
compared
traditional
methods,
across
various
fluorescent
samples
dense
structures.
Notably,
achieved
high-quality
3D
motion
hydra
neuronal
activity
cellular
awake
mouse
cortex.
DeepLeMiN
holds
great
promise
scalable,
large
FOV,
real-time,
applications
compact
footprint.
Язык: Английский
Automated cell profiling in imaging flow cytometry with annotation-efficient learning
Optics & Laser Technology,
Год журнала:
2024,
Номер
181, С. 111992 - 111992
Опубликована: Окт. 30, 2024
Язык: Английский
From Pixels to Information: Artificial Intelligence in Fluorescence Microscopy
Advanced Photonics Research,
Год журнала:
2024,
Номер
5(9)
Опубликована: Июль 15, 2024
This
review
explores
how
artificial
intelligence
(AI)
is
transforming
fluorescence
microscopy,
providing
an
overview
of
its
fundamental
principles
and
recent
advancements.
The
roles
AI
in
improving
image
quality
introducing
new
imaging
modalities
are
discussed,
offering
a
comprehensive
perspective
on
these
changes.
Additionally,
unified
framework
introduced
for
comprehending
AI‐driven
microscopy
methodologies
categorizing
them
into
linear
inverse
problem‐solving,
denoising,
nonlinear
prediction.
Furthermore,
the
potential
self‐supervised
learning
techniques
that
address
challenges
associated
with
training
networks
explored,
utilizing
unlabeled
data
to
enhance
expand
capabilities.
It
worth
noting
while
specific
examples
advancements
discussed
this
focus
general
approaches
theories
directly
applicable
other
optical
methods.
Язык: Английский
Full-Aperture Reflective Remote Fourier Ptychography with Sample Matching
Remote Sensing,
Год журнала:
2024,
Номер
16(22), С. 4276 - 4276
Опубликована: Ноя. 16, 2024
Fourier
ptychography
(FP)
can
break
through
the
limitations
of
existing
optical
systems
with
a
single
aperture
and
realize
large
field-of-view
(FOV)
high-resolution
(HR)
imaging
simultaneously
by
synthesis
in
frequency
domain.
The
method
has
potential
applications
for
remote
sensing
space-based
imaging.
However,
stop
system
was
generally
set
to
be
much
smaller
than
an
adjustable
diaphragm,
so
it
failed
make
full
use
capability
system.
In
this
paper,
reflective
FP
is
proposed,
camera
maximum
according
sample-matching
condition,
which
further
improve
resolution
exploring
whole
Firstly,
physical
model
established
using
oblique
illumination
convergent
spherical
wave.
Then,
sampling
characteristics
low-resolution
(LR)
intensity
image
are
analyzed.
Assuming
diffraction-limited
imaging,
size
needs
match
detector.
An
experimental
setup
distance
2.4
m
built,
series
LR
images
collected
moving
diffused
samples,
including
USAF
test
target
banknote,
where
diameter
CCD
pixel
under
practical
minimum
F#
2.8.
reconstructed
applying
iterative
phase
retrieval
algorithm.
results
show
that
improved
2.5×.
This
verifies
effectively
only
present
single-aperture
Язык: Английский