This frequency has small pixel-to-pixel count differences and represents background.
Low frequency
Butterworth is classified as this type of filter.
Low-pass filter
What does the “T” in SPECT stand for?
Tomography
This reconstruction method “smears” counts back along the radius from each projection.
Back projection
This is the highest useful frequency that can be sampled without causing distortion.
Nyquist frequency
A bone scan is dominated by this type of frequency component.
High frequency
This type of image data is primarily removed by a Butterworth low-pass filter.
High-frequency noise
This acquisition mode stops at each angle and does not collect counts while moving.
Step-and-shoot
This classic artifact appears as streaks radiating from hot structures.
Star artifact
The Nyquist frequency equals this many cycles per pixel.
0.5 cycles/pixel
This frequency shows large pixel-to-pixel differences and represents sharp edges and noise.
High frequency
This Butterworth setting determines how much high-frequency data is allowed through.
Cutoff frequency
This cardiac SPECT setting is based on the R-wave of the ECG.
Gating
This filter is always used with back projection.
Ramp filter
This imaging parameter directly determines the Nyquist frequency by controlling pixel size.
Matrix size
A gallium-67 scan contains this frequency range.
Low Frequency
Increasing the cutoff frequency will do this to image resolution and noise.
Increases resolution but increases noise
A dual-head camera only needs to rotate this many degrees to acquire a full dataset.
180°
The ramp filter is classified as this type of frequency filter.
High-pass filter
Decreasing pixel size will do this to the Nyquist frequency.
Increase it
The unwanted image component caused by statistical fluctuations and low counts.
Noise
In cardiac SPECT, improper Butterworth filter selection most directly affects this key image quality factor.
Spatial resolution
This type of orbit improves spatial resolution by keeping the camera closer to the patient.
Elliptical orbit
This is the main purpose of filtering after back projection.
To remove background and correct image blurring
At Nyquist, this sampling pattern occurs across the matrix.
Every other pixel is on