The problem of extracting spots from DNA microarrays is a problem of considerable scientific and economic utility. In this paper we introduce a new approach based on a scale-space analysis of the image. We augment this with a machine learning system that guides an operator by classifying spots into those that require further attention and those that are already segmented correctly. We compare conventional k-nearest neighbor techniques with generalized linear models and multilayer perceptrons using confidence intervals and McNemar's test.
|Number of pages||6|
|Publication status||Published - 2003|
|Event||Proceedings of the IEEE/INNS International Joint Conference on Artificial Neural Networks (IJCNN-2003) - Portland, OR|
Duration: 20 Jul 2003 → 24 Jul 2003
|Conference||Proceedings of the IEEE/INNS International Joint Conference on Artificial Neural Networks (IJCNN-2003)|
|Period||20/07/03 → 24/07/03|