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Mendeley readers
Chapter title |
Endoscope distortion correction does not (easily) improve mucosa-based classification of celiac disease.
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Chapter number | 71 |
Book title |
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012
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Published in |
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, January 2013
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DOI | 10.1007/978-3-642-33454-2_71 |
Pubmed ID | |
Book ISBNs |
978-3-64-233453-5, 978-3-64-233454-2
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Authors |
Hämmerle-Uhl J, Höller Y, Uhl A, Vécsei A, Hämmerle-Uhl, Jutta, Höller, Yvonne, Uhl, Andreas, Vécsei, Andreas |
Abstract |
Distortion correction is applied to endoscopic duodenal imagery to improve automated classification of celiac disease affected mucosa patches. In a set of six edge- and shape-related feature extraction techniques, only a single one is able to consistently benefit from distortion correction, while for others, even a decrease of classification accuracy is observed. Different types of distortion correction do not lead to significantly different behaviour in the observed application scenario. |
Mendeley readers
The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 8 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 4 | 50% |
Student > Bachelor | 2 | 25% |
Student > Ph. D. Student | 1 | 13% |
Other | 1 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Engineering | 3 | 38% |
Agricultural and Biological Sciences | 2 | 25% |
Sports and Recreations | 1 | 13% |
Computer Science | 1 | 13% |
Unknown | 1 | 13% |