| Title |
Edge map analysis in chest X-rays for automatic pulmonary abnormality screening
|
|---|---|
| Published in |
International Journal of Computer Assisted Radiology and Surgery, March 2016
|
| DOI | 10.1007/s11548-016-1359-6 |
| Pubmed ID | |
| Authors |
K. C. Santosh, Szilárd Vajda, Sameer Antani, George R. Thoma |
| Abstract |
Our particular motivator is the need for screening HIV+ populations in resource-constrained regions for the evidence of tuberculosis, using posteroanterior chest radiographs (CXRs). The proposed method is motivated by the observation that abnormal CXRs tend to exhibit corrupted and/or deformed thoracic edge maps. We study histograms of thoracic edges for all possible orientations of gradients in the range [Formula: see text] at different numbers of bins and different pyramid levels, using five different regions-of-interest selection. We have used two CXR benchmark collections made available by the U.S. National Library of Medicine and have achieved a maximum abnormality detection accuracy (ACC) of 86.36 % and area under the ROC curve (AUC) of 0.93 at 1 s per image, on average. We have presented an automatic method for screening pulmonary abnormalities using thoracic edge map in CXR images. The proposed method outperforms previously reported state-of-the-art results. |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 50 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 18% |
| Student > Master | 7 | 14% |
| Researcher | 5 | 10% |
| Student > Postgraduate | 4 | 8% |
| Student > Bachelor | 2 | 4% |
| Other | 5 | 10% |
| Unknown | 18 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 9 | 18% |
| Engineering | 9 | 18% |
| Medicine and Dentistry | 5 | 10% |
| Business, Management and Accounting | 1 | 2% |
| Biochemistry, Genetics and Molecular Biology | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 25 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 30 July 2019.
All research outputs
#7,557,690
of 23,053,613 outputs
Outputs from International Journal of Computer Assisted Radiology and Surgery
#225
of 860 outputs
Outputs of similar age
#107,556
of 300,379 outputs
Outputs of similar age from International Journal of Computer Assisted Radiology and Surgery
#8
of 25 outputs
Altmetric has tracked 23,053,613 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 860 research outputs from this source. They receive a mean Attention Score of 3.1. This one has gotten more attention than average, scoring higher than 53% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 300,379 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.