| Title |
Hybrid model for analysis of abnormalities in diabetic cardiomyopathy and diabetic retinopathy related images
|
|---|---|
| Published in |
SpringerPlus, April 2016
|
| DOI | 10.1186/s40064-016-2152-2 |
| Pubmed ID | |
| Authors |
Fahimuddin Shaik, Anil Kumar Sharma, Syed Musthak Ahmed |
| Abstract |
At present image processing methods hold a noteworthy position in unravelling various medical imaging challenges. The high risk disorders such as diabetic cardiomyopathy and diabetic retinopathy are considered as applications for proposed method. The dictum of this paper is on observing enhancement and segmentation of the cross sectional view of a blood capillary of a right coronary artery image of a diabetic patient and also retinal images. A hybrid model using hybrid morphological reconstruction technique as pre-processing with watershed segmentation method as post-processing is developed in this work. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 6 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 1 | 17% |
| Student > Bachelor | 1 | 17% |
| Professor | 1 | 17% |
| Student > Ph. D. Student | 1 | 17% |
| Researcher | 1 | 17% |
| Other | 0 | 0% |
| Unknown | 1 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 3 | 50% |
| Medicine and Dentistry | 1 | 17% |
| Computer Science | 1 | 17% |
| Unknown | 1 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 June 2016.
All research outputs
#18,462,696
of 22,876,619 outputs
Outputs from SpringerPlus
#1,261
of 1,850 outputs
Outputs of similar age
#219,057
of 299,172 outputs
Outputs of similar age from SpringerPlus
#108
of 146 outputs
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