Literature DB >> 11345095

Computerized breast thermography: study of image segmentation and temperature cyclic variations.

E Y Ng1, Y Chen, L N Ung.   

Abstract

Breast cancer is a common and dreadful disease in women. The surface temperature and the vascularization pattern of the breast could indicate breast diseases. Establishing the surface isotherm pattern of the breast and the normal range of cyclic variations of temperature distribution can assist in identifying the abnormal infrared images of diseased breasts. This paper investigates the cyclic variation of temperature and vascularization of the normal breast thermograms under a controlled environment. More than 50 Asian women, were examined and some of them have been examined continuously for two month. All together, not less than 800 thermograms were obtained. Before these thermograms can be analysed objectively via a computer algorithm, they must be digitized and segmented. The authors present a method to segment thermograms and extract the useful region from the background. After the image processing, these thermograms can be analysed and then the best time to perform an examination can be chosen. All these results are important for establishing a data bank of normal breast thermography, to choose the best time for an examination and as a systematic methodology for evaluating and analysing the abnormal breast thermography in the future.

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Mesh:

Year:  2001        PMID: 11345095     DOI: 10.1080/03091900010022247

Source DB:  PubMed          Journal:  J Med Eng Technol        ISSN: 0309-1902


  12 in total

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3.  Thermography based breast cancer detection using texture features and Support Vector Machine.

Authors:  U Rajendra Acharya; E Y K Ng; Jen-Hong Tan; S Vinitha Sree
Journal:  J Med Syst       Date:  2010-10-19       Impact factor: 4.460

4.  Segmenting breast cancerous regions in thermal images using fuzzy active contours.

Authors:  Hossein Ghayoumi Zadeh; Javad Haddadnia; Omid Rahmani Seryasat; Sayed Mohammad Mostafavi Isfahani
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5.  Supportive Noninvasive Tool for the Diagnosis of Breast Cancer Using a Thermographic Camera as Sensor.

Authors:  Marco Antonio Garduño-Ramón; Sofia Giovanna Vega-Mancilla; Luis Alberto Morales-Henández; Roque Alfredo Osornio-Rios
Journal:  Sensors (Basel)       Date:  2017-03-03       Impact factor: 3.576

6.  Evaluation of the diagnostic performance of infrared imaging of the breast: a preliminary study.

Authors:  Jane Wang; King-Jen Chang; Chin-Yu Chen; Kuo-Liong Chien; Yuh-Show Tsai; Yuh-Ming Wu; Yu-Chuan Teng; Tiffany Ting-Fang Shih
Journal:  Biomed Eng Online       Date:  2010-01-07       Impact factor: 2.819

7.  Evaluation of the diagnostic power of thermography in breast cancer using Bayesian network classifiers.

Authors:  Cruz-Ramírez Nicandro; Mezura-Montes Efrén; Ameca-Alducin María Yaneli; Martín-Del-Campo-Mena Enrique; Acosta-Mesa Héctor Gabriel; Pérez-Castro Nancy; Guerra-Hernández Alejandro; Hoyos-Rivera Guillermo de Jesús; Barrientos-Martínez Rocío Erandi
Journal:  Comput Math Methods Med       Date:  2013-05-22       Impact factor: 2.238

8.  Level set method for segmentation of infrared breast thermograms.

Authors:  N Golestani; M EtehadTavakol; Eyk Ng
Journal:  EXCLI J       Date:  2014-03-13       Impact factor: 4.068

9.  Thermography based breast cancer detection using texture features and minimum variance quantization.

Authors:  Marina Milosevic; Dragan Jankovic; Aleksandar Peulic
Journal:  EXCLI J       Date:  2014-11-04       Impact factor: 4.068

10.  Intelligent neonatal monitoring based on a virtual thermal sensor.

Authors:  Abbas K Abbas; Steffen Leonhardt
Journal:  BMC Med Imaging       Date:  2014-03-02       Impact factor: 1.930

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