Literature DB >> 22874350

Texture analysis software: integration with a radiological workstation.

Régis Duvauferrier1, Joan Bezy, Valérie Bertaud, Grégoire Toussaint, John Morelli, Jeremy Lasbleiz.   

Abstract

Image analysis is the daily task of radiologists. The texture of a structure or imaging finding can be more difficult to describe than other parameters. Image processing can help the radiologist in completing this difficult task. The aim of this article is to explain how we have developed texture analysis software and integrated it into a standard radiological workstation. The texture analysis method has been divided into three steps: definition of primitive elements, counting, and statistical analysis. The software was developed in C++ and integrated into a Siemens workstation with a graphical user interface. The results of analyses may be exported in Excel format. The software allows users to perform texture analyses on any type of radiological image without the need for image transfer by simply placing a region of interest. This tool has already been used to assess the trabecular network of vertebra. The integration of such software into PACS extends the applicability of texture analysis beyond that of a mere research tool and facilitates its use in routine clinical practice.

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Mesh:

Year:  2012        PMID: 22874350

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  4 in total

1.  Prediction of Clinical Pathologic Prognostic Factors for Rectal Adenocarcinoma: Volumetric Texture Analysis Based on Apparent Diffusion Coefficient Maps.

Authors:  Zhihua Lu; Lei Wang; Kaijian Xia; Heng Jiang; Xiaoyan Weng; Jianlong Jiang; Mei Wu
Journal:  J Med Syst       Date:  2019-11-07       Impact factor: 4.460

2.  Value of MRI texture analysis for predicting new Gleason grade group.

Authors:  Xiaojing He; Hui Xiong; Haiping Zhang; Xinjie Liu; Jun Zhou; Dajing Guo
Journal:  Br J Radiol       Date:  2021-03-11       Impact factor: 3.039

3.  Association between Texture Analysis Parameters and Molecular Biologic KRAS Mutation in Non-Mucinous Rectal Cancer.

Authors:  Sung Jae Jo; Seung Ho Kim; Sang Joon Park; Yedaun Lee; Jung Hee Son
Journal:  Taehan Yongsang Uihakhoe Chi       Date:  2020-08-13

4.  Texture Analysis in the Assessment of Rectal Cancer: Comparison of T2WI and Diffusion-Weighted Imaging.

Authors:  Ming Li; Xiaodan Xu; Pengjiang Qian; Heng Jiang; Jianlong Jiang; Jinbing Sun; Zhihua Lu
Journal:  Comput Math Methods Med       Date:  2021-09-15       Impact factor: 2.238

  4 in total

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