Ultrasound Imaging
337
16.4 S ince the attenuation coefficient of ultrasound waves generally increases
with increasing frequency (see Problem 16.3), explain how second harmonic
imaging, i.e., using f = 2 .
1
f as the detected frequency, increases the image
information.
16.5 L oad file “p_16_5.jpg” and display. A blood vessel is imaged by intravascular
ultrasound showing the inside wall and the outside wall surrounded by mostly
fat. Using MATLAB ® and file p_16_5.jpg representing the clinical data,
perform the following.*
a. Ca lculate the relative thickness of the vessel wall with respect to the vessel
diameter.
b. U sing the fact that the vessel will be pressed against the catheter and that
the catheter has a diameter of 5 mm, calculate the thickness of the vessel
wall.
16.6 I n laser photocoagulation of ventricular tachycardia, diseased heart muscle is denatured with the energy of laser light to destroy the electric activity of a section of the heart wall that is no longer conducting properly
because of cell death resulting from a heart attack. Load file “p_16_6.jpg”
and display. Figure “p_16_6” shows an ultrasound image of a laser photocoagulated section of the left ventricular wall of a heart seen through the
tissue in the fifth intracostal space of the chest. The heated and coagulated
tissue is significantly denser than the healthy heart muscle. The transducer
operated at 10 MHz. Use the seed growing algorithm to find the outline
of the coagulation lesion. Visually choose suitable seed points to start the
segmentation process.
16.7 I n Doppler flow measurement using ultrasound, the blood flowing toward the
transducer will result in a higher frequency than was originally sent in, while
blood flowing away from the transducer will give a decrease in ultrasound
frequency. Load file “p_16_7.jpg” and display. The blood flow in “p_16_7.jpg”
toward the transducer has the increase in frequency colored as blue, while
the flow away from the ultrasound transducer decreases the frequency and is
illustrated by red. Use the seed growing algorithm to find the perimeter of the
left ventricle, and the fraction of turbulent flow using seed and region growing
techniques described in Section 4.3. Visually choose some suitable seed points
to start the process. †
16.8 R ead image “p_16_8.jpg” and show the image. One of the critical assessments to identify the healthy growth of the baby is measuring the diameter
of the baby’s head. In this problem, we write MATLAB codes to perform this
automatically.
a. A pply Laplacian of Gaussian method to detect the edge of the skull of the
baby.
b. O nce, the baby’s head is detected, write the codes to find the diameter of
the head. Here, we define the diameter as the largest distance between two
points located on the head’s contour.
* Courtesy of Brett Fowler, Heineman Research Laboratory, Carolinas Medical Center, Charlotte, NC.
† Courtesy of Ardent Sound, Inc., Guided Therapy Systems, Inc., Mesa, AZ.
337
16.4 S ince the attenuation coefficient of ultrasound waves generally increases
with increasing frequency (see Problem 16.3), explain how second harmonic
imaging, i.e., using f = 2 .
1
f as the detected frequency, increases the image
information.
16.5 L oad file “p_16_5.jpg” and display. A blood vessel is imaged by intravascular
ultrasound showing the inside wall and the outside wall surrounded by mostly
fat. Using MATLAB ® and file p_16_5.jpg representing the clinical data,
perform the following.*
a. Ca lculate the relative thickness of the vessel wall with respect to the vessel
diameter.
b. U sing the fact that the vessel will be pressed against the catheter and that
the catheter has a diameter of 5 mm, calculate the thickness of the vessel
wall.
16.6 I n laser photocoagulation of ventricular tachycardia, diseased heart muscle is denatured with the energy of laser light to destroy the electric activity of a section of the heart wall that is no longer conducting properly
because of cell death resulting from a heart attack. Load file “p_16_6.jpg”
and display. Figure “p_16_6” shows an ultrasound image of a laser photocoagulated section of the left ventricular wall of a heart seen through the
tissue in the fifth intracostal space of the chest. The heated and coagulated
tissue is significantly denser than the healthy heart muscle. The transducer
operated at 10 MHz. Use the seed growing algorithm to find the outline
of the coagulation lesion. Visually choose suitable seed points to start the
segmentation process.
16.7 I n Doppler flow measurement using ultrasound, the blood flowing toward the
transducer will result in a higher frequency than was originally sent in, while
blood flowing away from the transducer will give a decrease in ultrasound
frequency. Load file “p_16_7.jpg” and display. The blood flow in “p_16_7.jpg”
toward the transducer has the increase in frequency colored as blue, while
the flow away from the ultrasound transducer decreases the frequency and is
illustrated by red. Use the seed growing algorithm to find the perimeter of the
left ventricle, and the fraction of turbulent flow using seed and region growing
techniques described in Section 4.3. Visually choose some suitable seed points
to start the process. †
16.8 R ead image “p_16_8.jpg” and show the image. One of the critical assessments to identify the healthy growth of the baby is measuring the diameter
of the baby’s head. In this problem, we write MATLAB codes to perform this
automatically.
a. A pply Laplacian of Gaussian method to detect the edge of the skull of the
baby.
b. O nce, the baby’s head is detected, write the codes to find the diameter of
the head. Here, we define the diameter as the largest distance between two
points located on the head’s contour.
* Courtesy of Brett Fowler, Heineman Research Laboratory, Carolinas Medical Center, Charlotte, NC.
† Courtesy of Ardent Sound, Inc., Guided Therapy Systems, Inc., Mesa, AZ.