Watershed Segmentation Algorithm Based on Morphological Gradient Reconstruction

2015 ◽  
Author(s):  
Baoan Han
Keyword(s):  
Segmentation Algorithm ◽  
Watershed Segmentation ◽  
Morphological Gradient ◽  
Gradient Reconstruction

An Improved Watershed Segmentation Algorithm for Bridge Image

2014 ◽  
Vol 513-517 ◽  
pp. 3691-3694 ◽  
Author(s):  
Qiang Qiang Li ◽  
Wei Li
Keyword(s):  
Extreme Points ◽  
Input Image ◽  
Segmentation Algorithm ◽  
Experimental Results ◽  
Watershed Algorithm ◽  
Region Merging ◽  
Watershed Segmentation ◽  
Morphological Gradient ◽  
Multiscale Algorithm ◽  
Local Extreme

In order to solve the problem of over-segmentation of traditional watershed algorithm, an improved watershed segmentation algorithm of the bridge image was proposed in this paper. First, the input image was filtered by top-hat transformation and bottom-hat transformation, and then, a multiscale algorithm for computing morphological gradient images is proposed, and the threshold for marker-extraction is automatically calculated according to the statistics of local extreme points in the gradient map. The watershed algorithm is applied on the modified gradient map to segment the image. Then, the over-segmentation regions of the initial watershed segmentation is settled by region merging based on fisher distance.Region merging is ended according to divergence principle. Many contrast experimental results verified the feasibility and validity of the method.

scholarly journals Diffusion Tensor Imaging Features of Watershed Segmentation Algorithm for Analysis of the Relationship between Depression and Brain Nerve Function of Patients with End-Stage Renal Disease

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Feng Zhu ◽  
Jiao Xu ◽  
Mei Yang ◽  
Haitao Chi
Keyword(s):  
End Stage Renal Disease ◽  
Diffusion Tensor ◽  
Segmentation Algorithm ◽  
Control Group ◽  
Nerve Function ◽  
Watershed Segmentation ◽  
Stage Renal Disease ◽  
End Stage ◽  
The Relationship ◽  
Esrd Patients

The aim of this research was to explore the relationship between depression and brain nerve function in patients with end-stage renal disease (ESRD) and long-term maintenance hemodialysis (MHD) based on watershed segmentation algorithm using diffusion tensor imaging (DTI) technology. A total of 29 ESRD patients with depression who received MHD treatment in the hemodialysis center of hospital were included as the research subjects (case group). A total of 29 healthy volunteers were recruited as the control group, and a total of 29 ESRD patients with depression and brain lesions were recruited as the control group (HC group). Within 24 h after hemodialysis, the blood biochemical indexes were collected before this DTI examination. All participants completed the neuropsychological scale (MoCA, TMT A, DST, SAS, and SDS) test. The original DTI data of all subjects were collected and processed based on watershed segmentation algorithm, and the results of automatic segmentation according to the image were evaluated as DSC = 0.9446, MPA = 0.9352, and IOU = 0.8911. Finally, the average value of imaging brain neuropathy in patients with depression in the department of nephrology was obtained. The differences in neuropsychological scale scores (PSQI, MoCA, TMTA, DST, SAS, and SDS) between the two groups were statistically significant ( P < 0.05 ). The differences of FA values in all the white matter partitions of Fu organs, except the cingulum of hippocampus (CgH) between the two groups, were statistically significant ( P < 0.05 ). ESRD and DTI quantitative detection under the guidance of watershed segmentation algorithm in MHD patients showed that ESRD patients can be early identified, so as to carry out psychological nursing as soon as possible to reduce the occurrence of depression, and then protect the brain nerve to reduce brain neuropathy.

A watershed segmentation algorithm based on an optimal marker for bubble size measurement

Measurement ◽  
2019 ◽  
Vol 138 ◽  
pp. 182-193 ◽  
Author(s):  
Hu Zhang ◽  
Zhaohui Tang ◽  
Yongfang Xie ◽  
Xiaoliang Gao ◽  
Qing Chen
Keyword(s):  
Bubble Size ◽  
Segmentation Algorithm ◽  
Size Measurement ◽  
Watershed Segmentation

Modified Multi - Scale Morphological Watershed Segmentation Algorithm of 2d Images Using Hill Climbing Techniques

2012 ◽  
Vol 1 (1) ◽  
pp. 33-38
Author(s):  
R. Chithra Devi ◽  
◽  
R. Ananda Devi ◽  
T. Saravana Kumar ◽  
◽  
...  
Keyword(s):  
Segmentation Algorithm ◽  
Hill Climbing ◽  
Watershed Segmentation ◽  
Multi Scale ◽  
2D Images

scholarly journals Automatic Quantification of Microvessels Using Unsupervised Image Analysis

1998 ◽  
Vol 17 (2) ◽  
pp. 83-92 ◽  
Author(s):  
Petter Ranefall ◽  
Kenneth Wester ◽  
Christer Busch ◽  
Per-Uno Malmström ◽  
Ewert Bengtsson
Keyword(s):  
Image Analysis ◽  
Segmentation Algorithm ◽  
Field Of View ◽  
Automatic Method ◽  
Watershed Segmentation ◽  
Test Set ◽  
Automatic Quantification ◽  
Component Size ◽  
Fully Automatic ◽  
Object Counting

An automatic method for quantification of images of microvessels by computing area proportions and number of objects is presented. The objects are segmented from the background using dynamic thresholding of the average component size histogram.To be able to count the objects, fragmented objects are connected, all objects are filled, and touching objects are separated using a watershed segmentation algorithm.The method is fully automatic and robust with respect to illumination and focus settings.A test set consisting of images grabbed with different focus and illumination for each field of view, was used to test the method, and the proposed method showed less variation than the intraoperator variation using manual threshold.Further, the method showed good correlation to manual object counting (r= 0.80) on an other test set.

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