NDLI: Bag-of-Visual-Ngrams for Histopathology Image Classification

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Bag-of-Visual-Ngrams for Histopathology Image Classification

Content Provider	CiteSeerX
Author	López-Monroy, A. Pastor Escalante, Hugo Jair Cruz-Roa, Angel González, Fabio A.
Abstract	This paper describes an extension of the Bag-of-Visual-Words (BoVW) representation for image classification (IC) of histophatology images. This representation is one of the most used approaches in several high-level computer vision tasks. However, the BoVW representation has an important limitation: the disregarding of spatial information among visual words. This information may be useful to capture discriminative visual-patterns in specific computer vision tasks. In order to overcome this problem we propose the use of visual n-grams. N-grams based-representations are very popular in the field of natural language processing (NLP), in particular within text mining and information retrieval. We propose building a codebook of n-grams and then representing images by histograms of visual n-grams. We evaluate our proposal in the challenging task of classifying histopathology images. The novelty of our proposal lies in the fact that we use n-grams as attributes for a classification model (together with visual-words, i.e., 1-grams). This is common practice within NLP, although, to the best of our knowledge, this idea has not been explored yet within computer vision. We report experimental results in a database of histopathology images where our proposed method outperforms the traditional BoVWs formulation.
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Access Restriction	Open
Subject Keyword	Histopathology Image Classification Histopathology Image N-grams Based-representations Specific Computer Vision Task Information Retrieval Image Classification Discriminative Visual-patterns Visual N-grams Traditional Bovws Formulation Histophatology Image Computer Vision Natural Language Processing Text Mining Important Limitation Classification Model Visual Word Several High-level Computer Vision Task Used Approach Common Practice Spatial Information Challenging Task Bovw Representation Experimental Result
Content Type	Text
Resource Type	Article

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