Toward embedded detection of polyps in WCE images for early diagnosis of colorectal cancer
International Journal of Computer Assisted Radiology and Surgery, ISSN: 1861-6429, Vol: 9, Issue: 2, Page: 283-293
2014
- 742Citations
- 157Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations742
- Citation Indexes741
- 741
- CrossRef27
- Patent Family Citations1
- 1
- Captures157
- Readers157
- 157
Article Description
Purpose: Wireless capsule endoscopy (WCE) is commonly used for noninvasive gastrointestinal tract evaluation, including the detection of mucosal polyps. A new embeddable method for polyp detection in wireless capsule endoscopic images was developed and tested. Methods: First, possible polyps within the image were extracted using geometric shape features. Next, the candidate regions of interest were evaluated with a boosting based method using textural features. Each step was carefully chosen to accommodate hardware implementation constraints. The method's performance was evaluated on WCE datasets including 300 images with polyps and 1,200 images without polyps. Hardware implementation of the proposed approach was evaluated to quantitatively demonstrate the feasibility of such integration into the WCE itself. Results: The boosting based polyp classification demonstrated a sensitivity of 91.0 %, a specificity of 95.2 % and a false detection rate of 4.8 %. This performance is close to that reported recently in systems developed for an online analysis of video colonoscopy images. Conclusion: A new method for polyp detection in videoendoscopic WCE examinations was developed using boosting based approach. This method achieved good classification performance and can be implemented in situ with embedded hardware. © 2013 CARS.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84897112495&origin=inward; http://dx.doi.org/10.1007/s11548-013-0926-3; http://www.ncbi.nlm.nih.gov/pubmed/24037504; http://link.springer.com/10.1007/s11548-013-0926-3; https://dx.doi.org/10.1007/s11548-013-0926-3; https://link.springer.com/article/10.1007/s11548-013-0926-3
Springer Science and Business Media LLC
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