A Survey on Enhanced RSA Algorithms
2019
The segmentation of diabetic plantar foot thermal images that are taken with no constraining
setup is a challenging problem. The present paper is dedicated to the comparison of three active
contour-based methods with prior shape information that are well suited to the given problem.
The first method was recently proposed by the present authors. It is based on the Kass et al.
method and on a new extra term that minimizes the difference between the curve curvature of
the active contour and the prior shape one. The second method is the Ahmed et al. one, a
Fourier-based method with prior shape matching. The third one was suggested by Chen et al.
where a geodesic snake is associated with a prior shape energy function. Using a database of
50 plantar foot thermal images, results show that our proposed method outperforms the two
others with a root-mean-square error (RMSE) equal to 5.12 pixels and a Dice Similarity
Coefficient (DSC) score of 93.9%. In addition, our method is robust to initial contour variations
and fast, therefore suitable for smartphone application in the context of diabetic foot problem.
Keywords:
- Curvature
- Active contour model
- Segmentation
- Dice
- Fourier transform
- Pixel
- Geodesic
- Artificial intelligence
- Computer science
- Mean squared error
- Pattern recognition
- polynomial classifier
- Communication channel
- Computer hardware
- encryption decryption
- Detector
- Ranging
- Cognitive radio
- Universal Software Radio Peripheral
- experimental laboratory
- Correction
- Source
- Cite
- Save
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