Volume segmentation using the Fourier surface method
3 views (last 30 days)
Show older comments
mohd akmal masud on 7 Jan 2023
Edited: mohd akmal masud on 18 Apr 2023
Dear all, anyone know is how to use the Fourier surface method for volume segmentation in SPECT imaging?
That method mention in this paper, on page 3. https://sci-hub.hkvisa.net/10.1186/s13550-017-0262-7
William Rose on 3 Mar 2023
@mohd akmal masud, No I have not done it.
The paper you cited has the relevant equations. They used a downhill simplex to adjust the unknown coefficients, to maximize B (tehir equation 4). You could use downhill simplex, but you could also use fmincon() which is a nice Matlab routine for minimization. Good luck!
Anshuman on 17 Apr 2023
Steps to perform volume segmentation using the FSM:
- First step is to acquire SPECT data for the object.
- The obtained SPECT data is preprocessed to remove noise, artifacts, and other unwanted features. This step includes filtering and normalization.
- Now we have to perfrom the image segmentation to separate the object from the background. FSM is a model-based image segmentation method that uses Fourier transforms to represent the surface of the object.
- Now the Fourier transform converts the SPECT data into the frequency domain, where the object's surface can be represented as a sum of Fourier coefficients.
- Fourier coefficients are thresholded to remove noise and other unwanted features.
- The thresholded Fourier coefficients are then transformed back to the spatial domain using the inverse Fourier transform. The resulting image represents the object's surface, which can be used to segment the volume of interest.
Hope it helps!
Find more on Image Segmentation and Analysis in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!Start Hunting!