Bartschat, Andreas and Toso, Lorenzo and Stegmaier, Johannes and Kuijper, Arjan and Mikut, Ralf and Köhler, Bernd and Allgeier, Stephan (2016):
Automatic Corneal Tissue Classification Using Bag-Of-Visual-Words Approaches.
KIT Scientific Publishing, Karlsruhe, In: Forum Bildverarbeitung 2016, Karlsruhe, 01.-02. Dezember 2016, [Conference or Workshop Item]
Abstract
Corneal confocal microscopy is a promising diagnostic method for peripheral neuropathy. It allows the recording of the sub-basal nerve plexus (SNP) and enables the morphological analysis of peripheral nerves. This work evaluates classification models for real-time evaluation of cornea images in order to find suitable methods for an automatic focus adaptation to the SNP. The analyzed Bag-of-Visual-Words method leads to models with an accuracy of 0.9, even on a small training dataset, and a runtime of 18 ms per image. Furthermore, the analysis of the support vector machine real-valued output shows high potential for the implementation of real-time focus optimization methods.
| Item Type: | Conference or Workshop Item |
|---|---|
| Erschienen: | 2016 |
| Creators: | Bartschat, Andreas and Toso, Lorenzo and Stegmaier, Johannes and Kuijper, Arjan and Mikut, Ralf and Köhler, Bernd and Allgeier, Stephan |
| Title: | Automatic Corneal Tissue Classification Using Bag-Of-Visual-Words Approaches |
| Language: | English |
| Abstract: | Corneal confocal microscopy is a promising diagnostic method for peripheral neuropathy. It allows the recording of the sub-basal nerve plexus (SNP) and enables the morphological analysis of peripheral nerves. This work evaluates classification models for real-time evaluation of cornea images in order to find suitable methods for an automatic focus adaptation to the SNP. The analyzed Bag-of-Visual-Words method leads to models with an accuracy of 0.9, even on a small training dataset, and a runtime of 18 ms per image. Furthermore, the analysis of the support vector machine real-valued output shows high potential for the implementation of real-time focus optimization methods. |
| Publisher: | KIT Scientific Publishing, Karlsruhe |
| Uncontrolled Keywords: | Guiding Theme: Individual Health, Research Area: Computer vision (CV), Image classification, Image processing |
| Divisions: | 20 Department of Computer Science 20 Department of Computer Science > Mathematical and Applied Visual Computing |
| Event Title: | Forum Bildverarbeitung 2016 |
| Event Location: | Karlsruhe |
| Event Dates: | 01.-02. Dezember 2016 |
| Date Deposited: | 08 May 2019 06:31 |
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