Name
Title | ||
|---|---|---|
Swarm Optimization and Multi-level Thresholding of Cytological Images for Breast Cancer Diagnosis. |
Abstract | ||
|---|---|---|
This paper presents a novel approach for multi-level thresholding of cytologic images. Typically, thresholding is applied in order to segment the image into regions of interest or objects, each having a high level of homogeneity in some parameter such as luminance. Homogeneous regions are then used to generate a set of features discriminating categories occurring in a given diagnostic problem. Instead of homogeneity measure, our approach uses a classifier to evaluate the quality of segmentation solution directly. The candidate solutions (sets of threshold values) are generated with use of the stochastic swarm intelligence-based metaheuristics. Experimental results demonstrate the promising performance of the proposed classification-driven segmentation in application to breast cancer diagnostics. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-319-00969-8_60 | PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON COMPUTER RECOGNITION SYSTEMS CORES 2013 |
Field | DocType | Volume |
Computer vision,Homogeneity (statistics),Pattern recognition,Swarm behaviour,Segmentation,Computer science,Swarm intelligence,Artificial intelligence,Thresholding,Classifier (linguistics),Luminance,Metaheuristic | Conference | 226 |
ISSN | Citations | PageRank |
2194-5357 | 1 | 0.36 |
References | Authors | |
10 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marek Kowal | 1 | 55 | 5.27 |
| Paweł Filipczuk | 2 | 100 | 6.44 |
| Andrzej Marciniak | 3 | 22 | 6.42 |
| Andrzej Obuchowicz | 4 | 76 | 10.10 |