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Presented by
Deepa Challa
Vijaya Lakshmi Boyina
Bhavani Duggineni
INTRODUCTION
 Neurons can be classified based on
-Direction of travel
-Neuron transmitter utilized
-Electro physiological properties
INTELLIGENT THRESHOLDING
 This technique helps to improve the average accuracy of
segmentation and makes the segmentation process more
consistent
 Involves three steps (1).Extracting features from sample images
(2).Training the neuronal network (3). Testing with new images
 Neuronal network means : In information technology, a neural
network is a system of programs and data structures that
approximates the operation of the human brain. Typically, a
neural network is initially "trained" or fed large amounts of data
and rules about data relationships
Resize
Image->Adjust->Threshold
TRANSECTED SEGMENTS AND
ADJACENT CELLS
 Neurons can be transected in to segments, it helps in
studying the specific parts of neuron by stripping the
unnecessary regions.
 Adjacent cells/neurons are the neurons that are
located beside each other. These neurons
communicates each other and separated by a space
called synapse.
SEED POINTS
 Seed point is a point against which information is
tagged
 Regional growing segmentation uses the concept of
seed points
 The initial region begins as the exact location of the
seeds
 Seed point selection is based on some user criterion
EXTENDABLE TO LARGER IMAGES
AND STAINING INCONSISTENCIES
 In imaging projects, the cells or specimen is focused
under confocal or fluorescent microscope. The quality
of images depends on staining of the cells and a
proper staining enables us to produce good images for
evaluation.
 The software embedded in confocal microscope allows
us to expand the images to larger size for analyzing
QUANTIFICATION OF NEURONS
 Measurement of cell volume and surface area were made
from a 3d confocal microscope image data set.
 The Cavalieri principle was used to estimate the volume of
the neuron, the surface area was estimated using the
method of the spatial grid.
 These new methods allow a detailed quantitative analysis
of an Individual neuron that has also been characterized
electro physiologicaly by current and/or voltage clamp
recordings, which offers the unique possibility of directly
correlating morphological data with the measured
biophysical properties of the same cell.
Neuron Identification
Original image
Inverted image
2D V/S 3D SEGMENTATION
 Segmentation can be done by various methods like




regional growing, intelligent threshold etc.
2D culture means sub culturing cells on sterile petridishes
and 3D culture means culturing cells on matrigel and also
provides the artificially created environment resemble the
invivo.
Compared to 2D, 3D culture is more accurate and
segmentation of neurons can be performed more precisely
in 3D
2D – Two dimensional
3D – Three dimensional
3D Image
Rotating 3D image 360 degrees
3D Image Rotation
References
 Pampaloni, F., E. G. Reynaud, et al. (2007). "The third
dimension bridges the gap between cell culture and live
tissue." Nat Rev Mol Cell Biol 8(10): 839-845.
edi 3d culture
 http://www.sciencedirect.com/science/article/pii/S1058674
183710165
 http://ieeexplore.ieee.org/xpl/abstractCitations.jsp?tp=&ar
number=295913&url=http%3A%2F%2Fieeexplore.ieee.org
%2Fxpls%2Fabs_all.jsp%3Farnumber%3D295913
 http://en.wikipedia.org/wiki/Region_growing
 http://www.irphouse.com/ijeee/ijeeev6n1_03.pdf