Name
Title | ||
|---|---|---|
Quantitative consensus of supervised learners for diffuse lung parenchymal HRCT patterns |
Abstract | ||
|---|---|---|
Automated lung parenchymal classification usually relies on supervised learning of expert chosen regions representative of the visually differentiable HRCT patterns specific to different pathologies (eg. emphysema, ground glass, honey combing, reticular and normal). Considering the elusiveness of a single most discriminating similarity measure, a plurality of weak learners can be combined to improve the machine learnability. Though a number of quantitative combination strategies exist, their efficacy is data and domain dependent. In this paper, we investigate multiple (N=12) quantitative consensus approaches to combine the clusters obtained with multiple (n=33) probability density-based similarity measures. Our study shows that hypergraph based meta-clustering and probabilistic clustering provides optimal expert-metric agreement. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1117/12.2008110 | Proceedings of SPIE |
Keywords | Field | DocType |
cluster ensemble,meta clustering | Meta clustering,Similarity measure,Pattern recognition,Hypergraph,Supervised learning,Differentiable function,Probabilistic clustering,Artificial intelligence,Learnability,Probability density function,Machine learning,Physics | Conference |
Volume | ISSN | Citations |
8670 | 0277-786X | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sushravya Raghunath | 1 | 1 | 2.85 |
| s p rajagopalan | 2 | 8 | 2.13 |
| Ronald A Karwoski | 3 | 24 | 7.43 |
| Brian J Bartholmai | 4 | 33 | 11.91 |
| Richard A. Robb | 5 | 645 | 238.12 |