Module 3: Biomedical Image Processing
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Projects a three-dimensional object onto a two-dimensional image.
X-ray penetrates tissues and create ‘shadogram’.
As visible light, X-rays loose a certain amount of energy when they pass through different
materials. X-ray radiography measures the amount of energy loss. Because this energy loss
differs for the different materials, we can see a certain contrast in the image. For example an
X-ray image shows high intensities for soft tissue and lower intensities where the X-rays passed
through bones.
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It is not possible to determine the depth of the any discontinuity.
A small increase in the possibility that a person exposed to X-rays will develop cancer
later in life.
Computed tomography (CT) scan
“Computed tomography,” or CT, refers to a computerized
x-ray imaging procedure in which a narrow beam of x-rays
is aimed at a patient and quickly rotated around the body,
producing signals that are processed by the machine’s
computer to generate cross-sectional images, or “slices.”
These slices are called tomographic images and can give a
clinician more detailed information than conventional
x-rays. Once a number of successive slices are collected
by the machine’s computer, they can be digitally “stacked”
together to form a three-dimensional (3D) image of the
patient that allows for easier identification of basic
structures as well as possible tumors or abnormalities.
Imaging principle: Unlike a conventional x-ray—which uses a fixed x-ray tube—a CT scanner uses a motorized
x-ray source that rotates around the circular opening of a donut-shaped structure called a gantry. During a CT
scan, the patient lies on a bed that slowly moves through the gantry while the x-ray tube rotates around the
patient, shooting narrow beams of x-rays through the body.
Tomography: a technique for displaying a representation of a cross section through a human body or other solid object
Cross-sectional imaging is usually used to refer to CT that view the body in cross-section i.e. as
axial (cross-sectional) slices.
Positron emission tomography
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Positron emission tomography, also called PET imaging or a PET scan, is a type of
nuclear medicine imaging.
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PET imaging uses small amounts of radioactive materials called radiotracers
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A PET scan measures important body functions, such as metabolism. It helps doctors
evaluate how well organs and tissues are functioning.
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By identifying changes at the cellular level, PET may detect the early onset of disease
before other imaging tests can.
● You will receive a tracer either through an injection, inhalation
(breathing it in), or through a pill or substance to swallow.
● You may need to wait a certain amount of time for the tracer to
travel through your body to the tissue or organ being diagnosed or
treated.
● A camera that detects radiation will be placed over your body to
collect information on how the tracer is acting in an organ or tissue.
A PET scan can compare a normal brain (left) with one affected by Alzheimer's disease (right). The loss of red
color with an increase in yellow, blue and green colors shows areas of decreased metabolic activity in the
brain due to Alzheimer's disease.
Ultrasound scanning
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Imaging principle: ultrasound image is produced based on the reflection of the waves
off of the body structures. The strength (amplitude) of the sound signal and the time it
takes for the wave to travel through the body provide the information necessary to produce
an image.
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The denser the object the ultrasound hits, the more of the ultrasound bounces back.
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This bouncing back, or echo, gives the ultrasound image its features. Varying shades
of gray reflect different densities
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An ultrasound scan can be used to view the uterus and ovaries during pregnancy and
monitor the developing baby's health diagnose a condition.
● The sonographer puts a lubricating gel onto the patient’s skin and places a transducer
over the lubricated skin.
● The transducer is moved over the part of the body that needs to be examined.
Magnetic resonance imaging (MRI)
Magnetic resonance imaging (MRI)
is a type of scan that uses strong
magnetic fields and radio waves to
How does an MRI scan work?
Most of the human body is made up of water molecules, which consist of
hydrogen and oxygen atoms. At the centre of each hydrogen atom is an even
smaller particle called a proton. Protons are like tiny magnets and are very
sensitive to magnetic fields.When you lie under the powerful scanner magnets,
the protons in your body line up in the same direction, in the same way that a
produce detailed images of the
magnet can pull the needle of a compass. You will not be able to feel this. Short
inside of the body.
bursts of radio waves are then sent to certain areas of the body, knocking the
protons out of alignment. When the radio waves are turned off, the protons
realign. This sends out radio signals, which are picked up by receivers. These
An MRI scanner is a large tube that
signals provide information about the exact location of the protons in the body.
contains powerful magnets. You lie
They also help to distinguish between the various types of tissue in the body,
inside the tube during the scan.
because the protons in different types of tissue realign at different speeds and
produce distinct signals. In the same way that millions of pixels on a computer
screen can create complex pictures, the signals from the millions of protons in the
body are combined to create a detailed image of the inside of the body.
Image brightness
Brightness refers to the overall lightness or darkness of an image.
Image contrast
While brightness refers to the overall lightness or darkness of an image, contrast
refers to the brightness difference between different objects or regions of the
image.
Image filtering and Enhancement
● When processing medical images, highlighting certain parts of the
image such as tumor-like regions would help physicians make a better
Image filtering and Enhancement
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Space-domain image enhancement techniques: point processing and mask processing
Point processing techniques: each pixel of the original (input) image at coordinates (x, y) is
processed to create the corresponding pixel at coordinates (x, y) in the enhanced image.
mask processing: not only the pixel at (x, y) coordinates of the original image but also some
neighboring pixels of this point are involved in generating the pixel at (x, y) coordinates in the
enhanced image
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filter, mask, kernel, template, window
Low-pass filters attenuate or eliminate high-frequency components (edges and
other sharp details).
provide a smooth version of the original image.
Used for smoothing, blurring, noise reduction, bridge small gaps in lines and
curves.
Disadvantages: Attenuate edges and some sharp details
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larger the mask becomes, the more attenuation in high-frequency components is
achieved.
Increasing the dimension of the mask to higher values will result in more blurring
effect.
Median filter
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When median filters are applied to an image, pixels whose values are very
different from their neighboring pixels will be eliminated.
By eliminating the effect of such odd pixels, values are assigned to the pixels
that are more representative of the values of the typical neighboring pixels in
the original image.
Avantage: reduce the random noise without eliminating the useful
high-frequency components such as edges.
Step 1: All pixels in the neighborhood of the pixel in the original image
(identified
by the mask) are inserted in a list.
Step 2: This list is sorted in ascending (or descending) order.
Step 3: The median of the sorted list (i.e., the pixel in the middle of the list) is
chosen as the pixel value for the processed image.
Reduce the noise in the image
without destroying the edges
● On the other hand, while median filter has also reduced the
noise, it has preserved the edges of the image almost entirely.
Again, this difference is due to the fact that the median filter
forces the pixels with distinct intensities to be more like their
neighbors and therefore eliminates isolated intensity spikes.
Such a smoothing criterion will not result in significant amount
of filtering across edges.
● Median filters, however, have certain disadvantages. When
the number of noisy pixels is greater than half of the total
pixels, median filters give a poor performance. This is
because, in such cases, median value will be much more
influenced by dominating noisy values than the non-noisy
pixels
Sharpening filters
● Sharpening filters are used to extract and highlight fine
details from an image and also to enhance some blurred
details.
● Three important types of sharpening filters: high-pass filters,
high-boost filters, and derivative filters.
● general rule of “positive in center and negative in peripherals
● High-pass filters only to extract edges, they might be the
right tools, but they are not the best filters to simply
improve the quality of a blurred image.
● This is again due to the fact that high-pass filters eliminate
all important low-pass components that are necessary for
an improved image. Another problem with high-pass filters
is the possibility of generating negative numbers as the
pixel values of the filtered image. This is due to the
negative numbers used in the applied mask.
Solution: “high boost.”
Image Histogram:
Histogram is the graphical representation of pixel intensity values in a digital image.
The horizontal axis of the
graph represents the tonal
variations, while the vertical
axis represents the total
number of pixels in that
particular tone.
The left side of the horizontal
axis represents the dark
areas, the middle represents
mid-tone values and the right
hand side represents light
areas. The vertical axis
represents the size of the
area (total number of pixels)
that is captured in each one
of these zones.
Image Histogram:
Histogram is the graphical representation of pixel intensity values in a digital image.
Image Histogram:
Histogram is the graphical representation of pixel intensity values in a digital image.
Histogram of Bright Image
The components of the histogram are biased towards the high side of the grayscale .
This shows that the brightness is high in the current image.
Histogram of Dark Image
The components of the histogram are concentrated on the low (dark) side of the grayscale. This shows
that the brightness is very low (dark image) in the current image.
Histogram of Low Contrast Image
The histogram will be narrow and will be centered towards the middle of the grayscale. This shows that
the contrast is low in the current image.
Histogram of High Contrast Image
The components of the histogram cover a broad range of the grayscale. This shows that the contrast is
high in the current image.
is it possible to modify one image based on the contrast of
another one?
Is it possible to modify one image based on the contrast of
another one?
Given images A, and B, it is possible to modify the contrast level of A
according to B.
Histogram matching
Histogram matching is useful when we want to unify the contrast
level of a group of images
We have image A as the input image and Image B as the target image. We want
to modify the histogram of A, based on the distribution of B.
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In the first step, we calculate both histogram and the equalized histogram
of both A, and B.
Then we need to map each pixel of A, based on the value of its equalized
histogram to the value of B.
So, for example for pixels with the intensity level of 0 in A, the corresponding
value of A equalized histogram is 4. Now, we take a look at the B equalized
histogram and find the intensity value corresponding to 4, which is 0. So we
map the 0 intensity from A to 0 from B. We continue for all intensity values of
A. If there is no map from the equalized histogram of A to B, we just need to
pick the nearest value.