iCube: A similarity-based data cube for medical images

Annibal, Luana Peixoto; Felipe, Joaquim Cezar; Ciferri, Cristina Dutra de Aguiar; Ciferri, Ricardo Rodrigues

doi:10.1109/cbms.2010.6042663

Cited by 5 publications

(10 citation statements)

References 6 publications

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“…We have presented a preliminary version of this study in [7]. Here, we extend that work by allowing the storage of several perceptual layers in the DW, and by extending the conventional ETL process and OLAP query processing to support these perceptual layers.…”

Section: Introductionmentioning

confidence: 92%

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A similarity-based data warehousing environment for medical images

Teixeira

Annibal

Felipe

et al. 2015

Computers in Biology and Medicine

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A core issue of the decision-making process in the medical field is to support the execution of analytical (OLAP) similarity queries over images in data warehousing environments. In this paper, we focus on this issue. We propose imageDWE, a non-conventional data warehousing environment that enables the storage of intrinsic features taken from medical images in a data warehouse and supports OLAP similarity queries over them. To comply with this goal, we introduce the concept of perceptual layer, which is an abstraction used to represent an image dataset according to a given feature descriptor in order to enable similarity search. Based on this concept, we propose the imageDW, an extended data warehouse with dimension tables specifically designed to support one or more perceptual layers. We also detail how to build an imageDW and how to load image data into it. Furthermore, we show how to process OLAP similarity queries composed of a conventional predicate and a similarity search predicate that encompasses the specification of one or more perceptual layers. Moreover, we introduce an index technique to improve the OLAP query processing over images. We carried out performance tests over a data warehouse environment that consolidated medical images from exams of several modalities. The results demonstrated the feasibility and efficiency of our proposed imageDWE to manage images and to process OLAP similarity queries. The results also demonstrated that the use of the proposed index technique guaranteed a great improvement in query processing.

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Section: Introductionmentioning

confidence: 92%

“…In Fig. 8(a), we use three intervals [1,3], [4,6], and [7,9], which represent the rings around each representative image of the ColorHistogram perceptual layer. In Fig.…”

Section: Improved Task (D): Improved Task Of Filtering By Distances Omentioning

confidence: 99%

A similarity-based data warehousing environment for medical images

Teixeira

Annibal

Felipe

et al. 2015

Computers in Biology and Medicine

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“…Para isso, as consultas utilizadas foram definidas em termos das classes propostas considerando cenários que envolvem apenas predicados de similaridade entre imagens e também cenários envolvendo predicados convencionais. De acordo com os resultados obtidos, quando comparada ao trabalho correlato descrito em (Annibal et al, 2010), a estratégia EspecialistaAcessaDW proveu uma melhora no desempenho do processamento de consultas que envolvem apenas predicados de similaridade entre imagens, com um ganho médio que variou de 55.57% até aproximadamente 82.16%. Já a estratégia UnificadaAcessaDW proveu um ganho de aproximadamente 76,76% em consultas que envolvem tanto predicados de similaridade entre imagens quanto convencionais.…”

Section: Motivação E Contribuiçõesunclassified

“…Ademais, as empresas não são asúnicas a se beneficiarem dessa tecnologia, visto que naárea médica, por exemplo, aplicações dessa natureza têm sido amplamente exploradas para auxiliar os médicos a elaborarem diagnósticos mais precisos, determinando tratamentos mais eficazes. Como resultado, as pesquisas nessaárea têm estudado a incorporação de dados multimídia ao DW, visando proporcionar uma nova gama de consultas OLAP (Annibal et al, 2010;Arigon et al, 2007;Chen et al, 2008;Jin et al, 2010;Wong et al, 2004).…”

Section: Capítulounclassified

“…Oferecer suporte a dados multimídia confere ao SSD uma capacidade maior de análise. Por essa razão, pesquisas recentes têm estudado a incorporação desse tipo de dado ao contexto de DW (Annibal et al, 2010;Arigon et al, 2007;Chen et al, 2008;Jin et al, 2010;Wong et al, 2004). Nesta dissertação de mestrado o focoé em um ambiente de DWing de imagens.…”

Section: Capítulo 3 Data Warehouse De Imagensunclassified

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Processamento de consultas analíticas com predicados de similaridade entre imagens em ambientes de data warehousing

Teixeira¹

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A data warehousing environment offers support to the decision-making process. It consolidates data from distributed, autonomous and heterogeneous information sources into one of its main components, the data warehouse. Furthermore, it provides efficient processing of analytical queries (i.e. OLAP queries). A conventional data warehouse stores only alphanumeric data. On the other hand, an image data warehouse stores not only alphanumeric data but also intrinsic features of images, thus allowing data warehousing environments to perform analytical similarity queries over images. This requires the development of strategies to provide efficient processing of these complex and costly queries. Although there are a number of approaches in the literature aimed at the development of bitmap index for data warehouses and metric access methods for the efficient processing of similarity queries over images, to the best of our knowledge, there is not an approach that investigate these two issues in the same setting. In this research, we fill this gap in the literature by introducing the following main contributions: (i) the proposal of the ImageDW-index, an optimization mechanism aimed at the efficient processing of analytical queries extended with similarity predicates over images; and (ii) definition of different processing strategies for image data warehouses using the ImageDW-index. In order to validate these main proposals, we also introduce two secondary contributions, as follows: (iii) the ImageDW-Gen, a data generator to populate image data warehouses; and (iv) the proposal of four query classes, each one enforcing different query processing costs associated to the similarity predicates in image data warehousing environments. Using the ImageDW-Gen, performance tests were carried out in order to investigate the advantages introduced by the proposed strategies, according to the query classes. Compared to the most related work available in the literature, the ImageDW-index provided a performance gain that varied from 55.57% to 82.16%, considering one of the proposed strategies.

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