Extracting the cell objects of red tide algae is the most important step in the construction of an automatic microscopic image recognition system for harmful algal blooms.This paper describes a set of composite method...Extracting the cell objects of red tide algae is the most important step in the construction of an automatic microscopic image recognition system for harmful algal blooms.This paper describes a set of composite methods for the automatic segmentation of cells of red tide algae from microscopic images.Depending on the existence of setae,we classify the common marine red tide algae into non-setae algae species and Chaetoceros,and design segmentation strategies for these two categories according to their morphological characteristics.In view of the varied forms and fuzzy edges of non-setae algae,we propose a new multi-scale detection algorithm for algal cell regions based on border-correlation,and further combine this with morphological operations and an improved GrabCut algorithm to segment single-cell and multicell objects.In this process,similarity detection is introduced to eliminate the pseudo cellular regions.For Chaetoceros,owing to the weak grayscale information of their setae and the low contrast between the setae and background,we propose a cell extraction method based on a gray surface orientation angle model.This method constructs a gray surface vector model,and executes the gray mapping of the orientation angles.The obtained gray values are then reconstructed and linearly stretched.Finally,appropriate morphological processing is conducted to preserve the orientation information and tiny features of the setae.Experimental results demonstrate that the proposed methods can effectively remove noise and accurately extract both categories of algae cell objects possessing a complete shape,regular contour,and clear edge.Compared with other advanced segmentation techniques,our methods are more robust when considering images with different appearances and achieve more satisfactory segmentation effects.展开更多
Graphical representation of DNA sequences is a key component in studying biological problems. In order to gain new insights in DNA sequences, this paper combined the digitized methods of single-base, base pairs and co...Graphical representation of DNA sequences is a key component in studying biological problems. In order to gain new insights in DNA sequences, this paper combined the digitized methods of single-base, base pairs and coding in triplet bases with the times of base appearing, and then a novel 4D graphical representation method of DNA sequences was put forward. It was a one-to-one correspondence of the arbitrary DNA sequence and 4D graphical representation, that avoided causing non-unique 4D graphical representation and overlapping lines. The method could reflect the biological information features of DNA sequence more comprehensively and effectively without any losses. Based on the 4D graphical representation, we used the geometric center of 4D graphical representation as eigenvalue of DNA sequences analyses, which kept the original features of the data, and then established the Euclidean distances and included angles between vectors＇ ter- minal point for similarity analyses of the first extron of the beta-globulin gene among 11 species. Finally, we established the graph of systematic hierarchical cluster analysis of 11 species to observe more easily the relationship between species. A positive outcome was reached, and the results were in accord with biological taxonomy, which also supported the rationality and effectiveness of the novel 4D graphical representation.展开更多
Path length calculation is a frequent requirement in studies related to graph theoretic problems such as genetics. Standard method to calculate average path length （APL） of a graph requires traversing all nodes in t...Path length calculation is a frequent requirement in studies related to graph theoretic problems such as genetics. Standard method to calculate average path length （APL） of a graph requires traversing all nodes in the graph repeatedly, which is computationally expensive for graphs containing large number of nodes. We propose a novel method to calculate APL for graphs commonly required in the studies of genetics. The proposed method is computationally less expensive and less time-consuming compared to standard method.展开更多
基金Supported by the National Natural Science Foundation of China(Nos.61301240,61271406)
文摘Extracting the cell objects of red tide algae is the most important step in the construction of an automatic microscopic image recognition system for harmful algal blooms.This paper describes a set of composite methods for the automatic segmentation of cells of red tide algae from microscopic images.Depending on the existence of setae,we classify the common marine red tide algae into non-setae algae species and Chaetoceros,and design segmentation strategies for these two categories according to their morphological characteristics.In view of the varied forms and fuzzy edges of non-setae algae,we propose a new multi-scale detection algorithm for algal cell regions based on border-correlation,and further combine this with morphological operations and an improved GrabCut algorithm to segment single-cell and multicell objects.In this process,similarity detection is introduced to eliminate the pseudo cellular regions.For Chaetoceros,owing to the weak grayscale information of their setae and the low contrast between the setae and background,we propose a cell extraction method based on a gray surface orientation angle model.This method constructs a gray surface vector model,and executes the gray mapping of the orientation angles.The obtained gray values are then reconstructed and linearly stretched.Finally,appropriate morphological processing is conducted to preserve the orientation information and tiny features of the setae.Experimental results demonstrate that the proposed methods can effectively remove noise and accurately extract both categories of algae cell objects possessing a complete shape,regular contour,and clear edge.Compared with other advanced segmentation techniques,our methods are more robust when considering images with different appearances and achieve more satisfactory segmentation effects.
基金The work was supported by the National Natural Science Foundation of China （Grant No. 11271163） and by the Fundamental Research Funds for the Central Universities （JUSRP51317B）.
文摘Graphical representation of DNA sequences is a key component in studying biological problems. In order to gain new insights in DNA sequences, this paper combined the digitized methods of single-base, base pairs and coding in triplet bases with the times of base appearing, and then a novel 4D graphical representation method of DNA sequences was put forward. It was a one-to-one correspondence of the arbitrary DNA sequence and 4D graphical representation, that avoided causing non-unique 4D graphical representation and overlapping lines. The method could reflect the biological information features of DNA sequence more comprehensively and effectively without any losses. Based on the 4D graphical representation, we used the geometric center of 4D graphical representation as eigenvalue of DNA sequences analyses, which kept the original features of the data, and then established the Euclidean distances and included angles between vectors＇ ter- minal point for similarity analyses of the first extron of the beta-globulin gene among 11 species. Finally, we established the graph of systematic hierarchical cluster analysis of 11 species to observe more easily the relationship between species. A positive outcome was reached, and the results were in accord with biological taxonomy, which also supported the rationality and effectiveness of the novel 4D graphical representation.
文摘Path length calculation is a frequent requirement in studies related to graph theoretic problems such as genetics. Standard method to calculate average path length （APL） of a graph requires traversing all nodes in the graph repeatedly, which is computationally expensive for graphs containing large number of nodes. We propose a novel method to calculate APL for graphs commonly required in the studies of genetics. The proposed method is computationally less expensive and less time-consuming compared to standard method.
