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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jun Kong Sertel, O. Shimada, H. Boyer, K. Saltz, J. Gurcan, M. |
| Copyright Year | 2007 |
| Description | Author affiliation: Ohio State Univ., Columbus (Jun Kong; Sertel, O.) |
| Abstract | In this paper, the development of a computer-aided system for the classification of grade of neuroblastic differentiation is presented. This automated process is carried out within a multi-resolution framework that follows a coarse-to-fine strategy. Additionally, a novel segmentation approach using the Fisher-Rao criterion, embedded in the generic expectation-maximization algorithm, is employed. Multiple decisions from a classifier group are aggregated using a two-step classifier combiner that consists of a majority voting process and a weighted sum rule using priori classifier accuracies. The developed system, when tested on 14,616 image tiles, had the best overall accuracy of 96.89%. Furthermore, multi-resolution scheme combined with automated feature selection process resulted in 34% savings in computational costs on average when compared to a previously developed single-resolution system. Therefore, the performance of this system shows good promise for the computer-aided pathological assessment of the neuroblastic differentiation in clinical practice. |
| File Size | 279501 |
| File Format | |
| ISBN | 9781424414369 |
| ISSN | 15224880 |
| DOI | 10.1109/ICIP.2007.4379881 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-09-16 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image segmentation Image resolution Pathology Image decomposition Biomedical computing Tiles Image analysis Data mining System testing Computational efficiency Classifier Combination Neuroblastoma Multi-resolution Image Segmentation Pattern Classification |
| Content Type | Text |
| Resource Type | Article |
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