Literature DB >> 9267592

Fuzzy logic in computer-aided breast cancer diagnosis: analysis of lobulation.

B Kovalerchuk1, E Triantaphyllou, J F Ruiz, J Clayton.   

Abstract

This paper illustrates how a fuzzy logic approach can be used to formalize terms in the American College of Radiology (ACR) Breast Imaging Lexicon. In current practice, radiologists make a relatively subjective determination for many terms from the lexicon related to breast cancer diagnosis. Lobulation and microlobulation of nodules are two important features in the ACR lexicon. We offer an approach for formalizing the distinction of these features and also formalize the description of intermediate cases between lobulated and microlobulated masses. In this paper it is shown that fuzzy logic can be an effective tool in dealing with this kind of problem. The proposed formalization creates a basis for the next three steps (i) extended verification with blinded comparison studies. (ii) the automatic extraction of the related primitives from the image, and (iii) the detection of lobulated and microlobulated masses based on these primitives.

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Year:  1997        PMID: 9267592     DOI: 10.1016/s0933-3657(97)00021-3

Source DB:  PubMed          Journal:  Artif Intell Med        ISSN: 0933-3657            Impact factor:   5.326


  8 in total

1.  Neural network approaches to grade adult depression.

Authors:  Subhagata Chattopadhyay; Preetisha Kaur; Fethi Rabhi; U Rajendra Acharya
Journal:  J Med Syst       Date:  2011-07-21       Impact factor: 4.460

2.  We work with them? Healthcare workers interpretation of organizational relations mined from electronic health records.

Authors:  You Chen; Nancy Lorenzi; Steve Nyemba; Jonathan S Schildcrout; Bradley Malin
Journal:  Int J Med Inform       Date:  2014-04-28       Impact factor: 4.046

3.  Introduction of a New Diagnostic Method for Breast Cancer Based on Fine Needle Aspiration (FNA) Test Data and Combining Intelligent Systems.

Authors:  Mohammad Fiuzy; Javad Haddadnia; Nasrin Mollania; Maryam Hashemian; Kazem Hassanpour
Journal:  Iran J Cancer Prev       Date:  2012

4.  Fuzzy logic selection as a new reliable tool to identify molecular grade signatures in breast cancer--the INNODIAG study.

Authors:  Tatiana Kempowsky-Hamon; Carine Valle; Magali Lacroix-Triki; Lyamine Hedjazi; Lidwine Trouilh; Sophie Lamarre; Delphine Labourdette; Laurence Roger; Loubna Mhamdi; Florence Dalenc; Thomas Filleron; Gilles Favre; Jean-Marie François; Marie-Véronique Le Lann; Véronique Anton-Leberre
Journal:  BMC Med Genomics       Date:  2015-02-07       Impact factor: 3.063

5.  Empirical Driven Automatic Detection of Lobulation Imaging Signs in Lung CT.

Authors:  Guanghui Han; Xiabi Liu; Nouman Q Soomro; Jia Sun; Yanfeng Zhao; Xinming Zhao; Chunwu Zhou
Journal:  Biomed Res Int       Date:  2017-03-29       Impact factor: 3.411

6.  Construction of Pancreatic Cancer Classifier Based on SVM Optimized by Improved FOA.

Authors:  Huiyan Jiang; Di Zhao; Ruiping Zheng; Xiaoqi Ma
Journal:  Biomed Res Int       Date:  2015-10-12       Impact factor: 3.411

7.  Differentiating small (≤1 cm) focal liver lesions as metastases or cysts by means of computed tomography: a case-study to illustrate a fuzzy logic-based method to assess the impact of diagnostic confidence on radiological diagnosis.

Authors:  Rossano Girometti; Francesco Fabris; Andrea Sgarro; Gloria Zanella; Serena Pullini; Lorenzo Cereser; Giuseppe Como; Chiara Zuiani; Massimo Bazzocchi
Journal:  Comput Math Methods Med       Date:  2014-01-27       Impact factor: 2.238

8.  Convolutional neural network for breast cancer diagnosis using diffuse optical tomography.

Authors:  Qiwen Xu; Xin Wang; Huabei Jiang
Journal:  Vis Comput Ind Biomed Art       Date:  2019-05-08
  8 in total

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