Literature DB >> 17271978

Liver CT-image retrieval based on Gabor texture.

C G Zhao1, H Y Cheng, Y L Huo, T G Zhuang.   

Abstract

Gabor schemes of image representation have shown great success in many texture related computer vision applications. This is mainly because the primitives of image representation in vision have a wavelet form similar to Gabor elementary functions (GEF's). We use Gabor approach to analyze the texture of liver CT-images and extract the corresponding feature vectors. Then, the feature vectors are used to facilitate content-based image retrieval (CBIR). In experiments, a batch of liver CT images containing several types of CT findings is collected, and retrieval results by Gabor texture are present.

Entities:  

Year:  2004        PMID: 17271978     DOI: 10.1109/IEMBS.2004.1403458

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  5 in total

1.  Automated retrieval of CT images of liver lesions on the basis of image similarity: method and preliminary results.

Authors:  Sandy A Napel; Christopher F Beaulieu; Cesar Rodriguez; Jingyu Cui; Jiajing Xu; Ankit Gupta; Daniel Korenblum; Hayit Greenspan; Yongjun Ma; Daniel L Rubin
Journal:  Radiology       Date:  2010-05-26       Impact factor: 11.105

2.  Automatic annotation of radiological observations in liver CT images.

Authors:  Francisco Gimenez; Jiajing Xu; Yi Liu; Tiffany Liu; Christopher Beaulieu; Daniel Rubin; Sandy Napel
Journal:  AMIA Annu Symp Proc       Date:  2012-11-03

3.  Content-based retrieval of focal liver lesions using bag-of-visual-words representations of single- and multiphase contrast-enhanced CT images.

Authors:  Wei Yang; Zhentai Lu; Mei Yu; Meiyan Huang; Qianjin Feng; Wufan Chen
Journal:  J Digit Imaging       Date:  2012-12       Impact factor: 4.056

4.  Computerized Prediction of Radiological Observations Based on Quantitative Feature Analysis: Initial Experience in Liver Lesions.

Authors:  Imon Banerjee; Christopher F Beaulieu; Daniel L Rubin
Journal:  J Digit Imaging       Date:  2017-08       Impact factor: 4.056

5.  Extraction of lesion-partitioned features and retrieval of contrast-enhanced liver images.

Authors:  Mei Yu; Qianjin Feng; Wei Yang; Yang Gao; Wufan Chen
Journal:  Comput Math Methods Med       Date:  2012-09-04       Impact factor: 2.238

  5 in total

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