bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2023,
Volume and Issue:
unknown
Published: Sept. 24, 2023
Abstract
The
ability
to
image
tissues
in
three-dimensions
(3-D)
with
label-free
molecular
contrast
at
mesoscale
would
be
a
valuable
capability
biology
and
biomedicine.
Here,
we
introduce
Raman
spectral
projection
tomography
(RSPT)
for
volumetric
imaging
sub-millimeter
spatial
resolution.
We
have
developed
RSPT
instrument
capable
of
providing
3-D
transparent
semi-transparent
samples.
A
computational
pipeline
multivariate
reconstruction
was
established
extract
information
from
data.
demonstrate
visualization
phantoms
various
complex
shapes
contrast.
Finally,
apply
as
novel
tool
gradients
extracellular
matrix
heterogeneities
fixed
live
tissue-engineered
constructs
explanted
native
tissues.
opens
new
possibilities
monitoring
Applied Physics B,
Journal Year:
2024,
Volume and Issue:
130(9)
Published: Aug. 29, 2024
Computational
methods
have
been
established
as
cornerstones
in
optical
imaging
and
holography
recent
years.
Every
year,
the
dependence
of
on
computational
is
increasing
significantly
to
extent
that
components
are
being
completely
efficiently
replaced
with
at
low
cost.
This
roadmap
reviews
current
scenario
four
major
areas
namely
incoherent
digital
holography,
quantitative
phase
imaging,
through
scattering
layers,
super-resolution
imaging.
In
addition
registering
perspectives
modern-day
architects
above
research
areas,
also
reports
some
latest
studies
topic.
codes
pseudocodes
presented
for
a
plug-and-play
fashion
readers
not
only
read
understand
but
practice
algorithms
their
data.
We
believe
this
will
be
valuable
tool
analyzing
trends
predict
prepare
future
holography.
Sensors,
Journal Year:
2025,
Volume and Issue:
25(7), P. 2040 - 2040
Published: March 25, 2025
Continuous
wave-diffuse
optical
tomography
(CW-DOT)
has
emerged
as
a
promising
non-invasive
neuroimaging
technique
for
assessing
brain
function.
Its
ability
to
provide
mapping
with
high
spatial
resolution
over
traditional
functional
near-infrared
spectroscopy
(fNIRS)
garnered
significant
interest
in
clinical
and
cognitive
neuroscience.
In
this
review,
we
critically
summarized
the
hardware,
reconstruction
algorithms,
applications
of
CW-DOT
human
mapping,
providing
an
up-to-date
overview
guidelines
future
studies
conduct
studies.
ScienceDirect,
PubMed,
Web
Science,
IEEE
Xplore
databases
were
searched
from
their
inception
up
1
July
2024.
A
total
83
articles
included
final
systematic
review.
The
review
focused
on
existing
hardware
systems,
algorithms
CW-DOT,
both
settings
Finally,
highlighted
current
challenges
potential
directions
research,
including
absence
standardized
protocols
pressing
need
enhanced
quantitative
precision.
This
underscores
sophisticated
capabilities
particularly
realm
imaging.
Extensive
neuroscience
research
attested
technique's
anatomical
precision
reliability,
establishing
it
potent
instrument
practice.
The Journal of Physical Chemistry B,
Journal Year:
2024,
Volume and Issue:
unknown
Published: July 11, 2024
The
intimate
relationship
between
neuronal
activity
and
cerebral
oxygenation
underpins
fundamental
brain
functions
like
cognition,
sensation,
motor
control.
Optical
imaging
offers
a
noninvasive
approach
to
assess
often
serves
as
an
indirect
proxy
for
activity.
However,
deciphering
neurovascular
coupling─the
intricate
interplay
activity,
blood
flow,
oxygen
delivery─necessitates
independent,
high
spatial
resolution,
temporal
resolution
measurements
of
both
microvasculature
activation.
This
Perspective
examines
the
established
optical
techniques
employed
imaging,
specifically
functional
near-infrared
spectroscopy,
photoacoustic
coherence
tomography,
two-photon
phosphorescent
lifetime
microscopy,
highlighting
their
principles,
strengths,
limitations.
Several
other
emerging
are
also
introduced.
Finally,
we
discuss
key
technological
challenges
future
directions
quantitative
paving
way
deeper
understanding
metabolism
in
brain.
Medical Physics,
Journal Year:
2024,
Volume and Issue:
51(7), P. 4838 - 4858
Published: Jan. 12, 2024
Abstract
Background
A
variety
of
deep
learning‐based
and
iterative
approaches
are
available
to
predict
Tracer
Kinetic
(TK)
parameters
from
fully
sampled
or
undersampled
dynamic
contrast‐enhanced
(DCE)
MRI
data.
However,
both
the
methods
offer
distinct
benefits
drawbacks.
Purpose
To
propose
a
hybrid
algorithm
(named
as
‘Greybox'),
using
model‐
well
DL‐based,
for
solving
multi‐parametric
non‐linear
inverse
problem
directly
estimating
TK
DCE
data,
which
is
invariant
undersampling
rate.
Methods
The
proposed
was
inspired
by
plug‐and‐play
algorithms
used
linear
imaging
problems.
This
technique
tested
its
effectiveness
in
nonlinear
ill‐posed
generating
3D
parameter
maps
four‐dimensional
(4D;
Spatial
+
Temporal)
retrospectively
k‐space
learns
prior
UNET
estimate
based
on
Patlak
pharmacokinetic
model,
this
trained
utilized
an
gradient‐based
optimization
scheme.
Unlike
existing
DL
models,
network
rate
input
method
compared
with
total
variation‐based
direct
reconstruction
brain,
breast,
prostate
DCE‐MRI
datasets
various
rates
Radial
Golden
Angle
(RGA)
For
breast
dataset,
indirect
estimation
Fast
Composite
Splitting
comparison.
Undersampling
8,
12
20
were
experiments,
results
PSNR
SSIM
metrics.
dataset
10
patients,
data
four
patients
training
(1032
samples),
two
validation
(752
entire
volume
testing.
Similarly,
18
(720
five
(216
whole
three
brain
nineteen
ten
(3152
(1168
Statistical
tests
also
conducted
assess
significance
improvement
performance.
Results
experiments
showed
that
Greybox
performs
significantly
better
than
other
methods.
improved
estimated
terms
peak
signal‐to‐noise
ratio
up
3
dB
standard
Conclusion
algorithm,
Greybox,
can
provide
state‐of‐the‐art
performance
DCE‐MRI.
first
kind
utilize
convolutional
neural
network‐based
encodings
part
priors
improve
algorithm.
