3D imaging uses rotating X-ray beams to generate multiplanar and 3D surface rendered images, providing higher sensitivity than 2D imaging. 3D imaging allows isolated visualization of anatomical structures without overlap and provides anatomically accurate images that can be manipulated from various angles. Image reconstruction in CBCT involves acquiring projection images from multiple angles, preprocessing the data, filtering it using mathematical algorithms, and backprojecting the data to reconstruct axial slice images. Artifacts like beam hardening can be reduced using advanced reconstruction algorithms that correct for the hardening effect during iterations.

1. PRESENTED BY:
DR GAYATRI MEHROTRA

2. 2D 3D
Whats the difference between 2D and 3D
technology ?????
Improved
Diagnosis And
Treatment Plan
Better Patient
Communication
Increased Case
Acceptance
ADVANTAGES OF
3D

3.  While 2D radiographs are a static image
taken of a specific area of interest, 3D
imaging uses rotating cone shaped beams
of X-rays to take images that are then
reconstructed to form multiplanar images,
cross sectionals and 3D surface renderings
that have much higher sensitivity in
diagnosing pathology.

4. Categories 2D Imaging 3D Imaging
Images Flat Image MPR and cross
sectional images made
up of multiple thin
slices
Distinction of
structures
Anatomical structures
are overlapped
Isolated visualization
of structures
Clarity Distortions are
possible
Anatomical accuracy
can be achieved
Image Manipulation Single image for
manipulation
DICOM stacks
available for
manipulation

5.  X-rays are generated in a ray source, sent
through the object under investigation, so
that they project the object structure onto
some X-ray sensitive material, such as
chemical film, that transforms incoming X-
radiation into an image.
X ray
source
X
R
A
Y
F
I
L
M
2D

6.  Nowadays, projection images can be
acquired using high-resolution digital
detectors that involve semi- conductor
technology instead of using chemical film.

8.  The objective of CT is to convert a set of
projection images of an object, obtained
from various viewing directions, into a
representation of object structure

9.  Previously, CT machines would not have a
ring of detectors but a flat moving area
which would receive the rays emitted form
the x-ray tube.
 However, the problem is that to get a
perfect reconstrution of the object, needs
360 to 3600 images which leads to slow and
high-memory consuming process.

10.  Thus, by applying the projection and back
projection techniques not only helps to
reconstruct an image , but to do the process
in a fast and feasible manner.

11.  In CBCT units the radiation beam is 3-D in
shape and similar in photon energy to that
used in conventional and digital
radiography.
 As the source and receptor rotate once
around the patient, many exposures are
made, ranging in duration between 8.9 and
40 seconds.

12.  The software “reconstructs” the sum of the
exposures via algorithms specified by the
manufacturer into as many as 512 axial
slice images.

14.  Image production by CBCT involves four
steps:
Image acquisition
Image detection
Image reconstruction
Image display

15. PRE-PROCESING
REFORMATTED RAW DATA
CONVOLUTIONWITH FILTER
IMAGE RECONSTRUCTIONALGORITHM
RECONSTRUCTED IMAGE
IMAGE:
STORAGE
DISPLAY
RECORDING
ARCHIVING
DETECTORS
MECHANISM

16.  Raw Data- It’s The Result Of Scan Data
Being Pre-processed
 Convolved Data- Raw Data Is Filtered
Using Mathematical Filter Or Kernel
(Convolution)
 It Removes Blurr. Convolution Can Only
Be Applied To Raw Data.

17. RAW DATA

18.  Image Data ( Reconstructed Data)-
Convolved Data That Have Been
Backprojected Into The Image Matrix To
Create Ct Images Displayed On The
Monitor.

19.  IMAGE RECONSTRUCTION:
 It is the process of creating a volumetric
data set from the acquired basis and;
consists of two stages;i.e.; acquisition and
reconstruction stage.

21.  Acquisition is the process of creating a
volumetric data set from the acquired basic
projection frames.
 Single cone beam rotation takes less than 30
sec to produce 100 to more than 600
individual projection frames.
 Each basis projection image consists of
millions of pixels with 12 to 16 bits of data
assigned to each pixel.

22.  Because of limitations in X-ray detection
and registration, raw images from CBCT
detectors innately demonstrate variations of
both dark image offset and pixel gain as
well as pixel imperfections.
 Dark image offset is the accumulation of
charge by the detector while it is idle,
whereas gain is due to variations in
sensitivity across the detector.

23.  To compensate for the resulting
inhomogeneities, raw images require
systematic offset and gain calibration as
well as a correction to help hide defective
pixels.
 The sequence of the required calibration
steps is referred to as detector pre-
processing and requires the acquisition of
additional image sequences.

25.  Image reconstruction is a technique to
reconstruct an image from multiple
projections.
 The reconstructed image represents the
relative X-ray attenuation (i.e. the
reduction of beam intensity owing to X-ray
interactions) of the different materials in
the object.

26.  In CBCT, the scanned object is
reconstructed as a 3D matrix of voxels with
each voxel being assigned a grey value
depending on the
attenuation of
the material(s) inside
it.

27.  Image reconstruction can be grouped into
 three categories:
 Filtered back projection (FBP),
 Algebraic reconstruction techniques (ARTs)
and
 Statistical methods.

28.  In reconstruction, corrected images are
converted into a sinogram.
 A sinogram is a composite image developed
by extracting a row of pixels from each
projection image – called as radon
transformation.
 The resulting image is comprised of
multiple sine waves of different amplitude.

29.  The sinogram is reconstructed with a
filtered back-projection algorithm called
Feldkamp algorithm by a process called
Inverse Radon transformation.
 After reconstruction; the slices are
combined into a volume for visualization

30.  Common artifact is beam hardening
 Basic reconstruction algorithms commonly
assume a mono-energetic beam; therefore,
regions adjacent to, or surrounded by,
structures that cause beam hardening are
falsely considered as radiolucent because
the beam passed through them with relative
little absorption.

31.  Thus, these regions will appear darker.
 Beam hardening can occur at any beam
energy and for any material and tends to be
more pronounced for low energy beams and
for denser materials.

32. Physics of metal artifacts: (A) CT uses a polychromatic X-ray beam. As the
polychromatic beam passes through an object, the effective energy is shifted toward
higher values; thus, the beam progressively becomes “harder” as it traverses the
object. For a given material, the mass attenuation coefficient varies according to the
hardness of the incident beam. Materials, such as metal, with a higher mass
attenuation coefficient result in significantly more pronounced beam hardening. The
calculated CT number is therefore technically “in error” and results in beam
hardening artifact

33. (B). Beam hardening causes an error in the data received at the detector as shown. The
projected data value of the monochromatic beam is proportional to its pass length. By
contrast, the polychromatic beam results in a smaller value compared to the result
expected for a monochromatic beam. This differential—an error in the projected data
value—causes artifacts in the final image. The degree of error—and the resultant
artifact—depends on the mass attenuation coefficient and the thickness (the pass
length) of the object.

34.  Beam hardening can be (partially)
corrected during calibration and/or
through the use of advanced iterative
reconstruction algorithms, which, during
each iteration, estimate the extent of beam
hardening and correct for it.

35.  Use of 3D back projection in helical
scanning (as in the Feldkamp method) can
help compensate for the divergence of the
X-ray beam, consequently minimizing the
cone beam artifact

36.  While projection data are a summation of
linear attenuation coefficients along a ray
path that can be called forward projection,
FBP (and the FDK algorithm) is basically
the inverse or back projection process of
the weighted and filtered projections, in
which the value for each pixel in the
projection image is assigned to every voxel
along the path of the X-ray.

37. Areas of raw Data
with low photon
count
Metal Artifact
Fewer photons can
transverse metal
because of higher
attenuation
Postprocessing
image filters can
help to correct
raw data in
areas of low
photon count.

39.  Convolution Back projection used to
improve image quality and shorten
processing time (used by Shepp & Logan)
 Developed By:
 Ramchandran
 Lakshminarayanan
 Also Called Summation Method Or Linear
Superposition Method

40.  Backprojection is the simplest
reconstruction procedure.
 BP produces a spoke-line pattern blurring
details.
 Finite number of projections produces
streaking artifacts.

41. Spoke
like
pattern

43. Example: Projection

44. Example: Backprojection

45. Example: Backprojection

46. Idea behind the
reconstruction

48. Example image of how a cube
generates different projections
depending on the angle of projection

51.  Projection profile is filtered or convolved to
remove the typical star like blurring that is
characteristic of the simple back projection.
 Direct back-projection results in blurred
image
 Filter projection profiles prior to back
projection

53. Example- Backprojection

54. Example- Filtering

55. Example- Filtered
Backprojection

56.  All Projection Profiles Are Obtained
 The Logarithm Of Data Is Obtained
 Logarithmic Values Are Multiplied By
Digital Filter
 Filtered Profiles Are Backprojected
 The Filtered Projections Are Summed And
The Negative And Positive Components Are
Cancelled

60. Original
Back
Projection 1°
Filtered back
Projection 1°
Filtered back
Projection 10°