Spatial-HMM : A new approach for semantic annotation of histological images
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 22_Publication in policy or professional journal
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Article number | 1699928 |
| Pages (from-to) | 663-666 |
| Journal / Publication | Proceedings - International Conference on Pattern Recognition |
| Volume | 4 |
| Publication status | Published - 2006 |
Conference
| Title | 18th International Conference on Pattern Recognition, ICPR 2006 |
|---|---|
| Place | China |
| City | Hong Kong |
| Period | 20 - 24 August 2006 |
Link(s)
Abstract
This paper presents a new spatial-HMM for automatically classifying and annotating histological images. Our model is a 2D generalization of HMM. Given a matrix of feature vectors for all blocks in an image, the most appropriate semantic labels determined by our models are used for annotation. Our experimental results showed that our model is superior to HMM in both recognition and annotation accuracy. © 2006 IEEE.
Citation Format(s)
Spatial-HMM: A new approach for semantic annotation of histological images. / Feiyang, Yu; Ip, Horace H. S.
In: Proceedings - International Conference on Pattern Recognition, Vol. 4, 1699928, 2006, p. 663-666.
In: Proceedings - International Conference on Pattern Recognition, Vol. 4, 1699928, 2006, p. 663-666.
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 22_Publication in policy or professional journal
