Smart videocapsule for early diagnosis of colorectal cancer: Toward embedded image analysis
Computational Intelligence in Digital and Network Designs and Applications, Page: 325-350
2015
- 12Citations
- 7Captures
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.
Book Chapter Description
Wireless capsule endoscopy (WCE)enables screening of the gastrointestinal tract by a swallowable imaging system. However, contemporary WCE systems have several limitations-battery, lowprocessing capabilities, among others-which often result in low diagnostic yield. In this chapter, after a technical presentation of the components of a standard WCE, the authors discuss the related limitations and introduce a new concept of smart capsule with embedded image processing capabilities based on a boosting approach using textural features.We discuss the feasibility of the hardware integration of the detection-recognition method, also with respect to the most recent FPGA technologies.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84943613224&origin=inward; http://dx.doi.org/10.1007/978-3-319-20071-2_12; https://link.springer.com/10.1007/978-3-319-20071-2_12; https://doi.org/10.1007%2F978-3-319-20071-2_12; https://dx.doi.org/10.1007/978-3-319-20071-2_12; https://link.springer.com/chapter/10.1007/978-3-319-20071-2_12
Springer Science and Business Media LLC
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