Abstract
Watershed transform (WST) based methods are applied most widely in two-dimensional gel electrophoresis (2DGE) images segmentation. Mark controlled WST can accurately detect most protein spots except a few dense spots with various volumes and shapes. Without consideration of the spot shape, the external mark sometimes locates in the spot area and leads to incorrect segmentation. To overcome the problem, an improved WST algorithm based on 2DGE image priors was proposed in this paper. Firstly, it was to extract spot center marks according to the gray minimum prior and to dilate the center marks iteratively to get distance mark. Secondly, it was extract local nature mark in blocks divided by distance mark according to background gray maximum prior. Then, the distance mark and nature mark are fused to generate background mark. At last, WST was applied on the grads image to detect protein spot edges. Four experiments were carried on 4 real scanned 2DGE images and the results show that the proposed segmentation algorithm enhances the accuracy of the algorithm effectively[7].
Original language | English |
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Pages (from-to) | 145-149 |
Number of pages | 5 |
Journal | Bandaoti Guangdian/Semiconductor Optoelectronics |
Volume | 36 |
Issue number | 1 |
State | Published - 1 Feb 2015 |
Keywords
- 2DGE
- Data fusion
- Image prior
- Image segment
- Watershed transform