Semi-supervised Learning in Medical Image Database

Authors:
Chun Hung Li;Pong Chi Yuen
Affiliations:
-;-
Venue:
PAKDD '01 Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining
Year:
2001

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Abstract

This paper presents a novel graph-based algorithm for solving the semi-supervised learning problem. The graph-based algorithm makes use of the recent advances in stochastic graph sampling technqiue and a modeling of the labeling consistency in semi-supervised learning. The quality of the algorithm is empirically evaluated on a synthetic clustering problem. The semi-supervised clustering is also applied to the problem of symptoms classification in medical image database and shows promising results.