Unsupervised texture segmentation using Gabor filters
Pattern Recognition
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Keyword Spotting in Poorly Printed Documents using Pseudo 2-D Hidden Markov Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Linguistic Indexing of Pictures by a Statistical Modeling Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Medical Image Annotation and Retrieval Using SECC
CBMS '06 Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems
Image classification by a two-dimensional hidden Markov model
IEEE Transactions on Signal Processing
Histological image retrieval based on semantic content analysis
IEEE Transactions on Information Technology in Biomedicine
IEEE Transactions on Information Technology in Biomedicine
Classification of binary random patterns
IEEE Transactions on Information Theory
Nonlinear operator for oriented texture
IEEE Transactions on Image Processing
Comparison of texture features based on Gabor filters
IEEE Transactions on Image Processing
Generalized Relevance Models for Automatic Image Annotation
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Content-based histopathology image retrieval using a kernel-based semantic annotation framework
Journal of Biomedical Informatics
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
Automatic Image Annotation Based on Generalized Relevance Models
Journal of Signal Processing Systems
Histology image indexing using a non-negative semantic embedding
MCBR-CDS'11 Proceedings of the Second MICCAI international conference on Medical Content-Based Retrieval for Clinical Decision Support
Biological interpretation of morphological patterns in histopathological whole-slide images
Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine
Support vector description of clusters for content-based image annotation
Pattern Recognition
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This paper presents a novel two-dimensional (2-D) stochastic method for semantic analysis of the content of histological images Specifically, we propose a 2-D generalization of the traditional hidden Markov model (HMM). The generalization is called spatial-hidden Markov model (SHMM) that captures the contextual characteristics of complex biological features in histological images The model employs a second-order neighborhood system and assumes the conditional independence of vertical and horizontal transitions between hidden states. The notion of 'past' in SHMM is defined as what have been observed in a row-wise raster scan. This paper focuses on two fundamental problems: the best states decoding problem and the estimation of generation probability of an image by a SHMM. Based on our independence assumption of horizontal and vertical transitions, we derive computational tractable solutions to those problems. These solutions are direct extensions of their counterparts, i.e., the Viterbi algorithm and Forward-Backward algorithm, for 1-D HMM. Our experiments were carried on a medical image database with 200 images and compared with a state-of-the-art approach that was run on the same database. The annotation results demonstrated that SHMM consistently outperforms the previous approach and ameliorates many of its drawbacks. In addition, performance comparison with HMM has also validated the superiority of SHMM.