Name
Abstract | ||
|---|---|---|
The ability to automatically monitor the wound healing process would reduce the workload of professionals, provide standardization, reduce costs, and improve the quality of care for patients. Here we propose an automatic monitoring system for leg ulcers based on case-based reasoning. We focus on the first stage of the monitoring process in this work, that of tissue classification and examine a number of different feature extraction techniques based on texture and Red, Green, and Blue histograms. Results clearly show a case-based approach to be ideal for this type of task. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/CBMS.2005.39 | CBMS |
Keywords | Field | DocType |
wound healing process,different feature extraction technique,case-based tissue classification,automatic monitoring system,leg ulcer,monitoring leg ulcer healing,tissue classification,monitoring process,case-based reasoning,blue histogram,case-based approach,standardization,case based reasoning,skin,image classification,histograms,leg,case base reasoning,patient monitoring,feature extraction | Ulcer healing,Histogram,Data mining,Workload,Computer science,Remote patient monitoring,Feature extraction,Case-based reasoning,Contextual image classification,Standardization | Conference |
ISSN | ISBN | Citations |
2372-9198 | 0-7695-2355-2 | 14 |
PageRank | References | Authors |
0.93 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. Galushka | 1 | 14 | 0.93 |
| Huiru Zheng | 2 | 458 | 74.87 |
| D. Patterson | 3 | 21 | 2.62 |
| L. Bradley | 4 | 14 | 1.27 |