Literature DB >> 11452633

Numerical computation as a tool to aid thermographic interpretation.

E Y Ng1, N M Sudharsan.   

Abstract

Thermography is an non-invasive and a painless tool for the detection of breast cancer. However, performing and interpreting thermograms requires meticulous training. It was found that women with an abnormal thermogram are at a higher risk and have a poorer prognosis. One of the main drawbacks of the thermogram is the high incidence of false-positive results. The authors believe that the fault lies in misinterpretation of the thermogram, rather than the thermogram itself. The paper aims to show that computer simulations could be an adjunct tool to help the clinician in the interpretation. This would greatly reduce the false-positive diagnosis.

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Year:  2001        PMID: 11452633     DOI: 10.1080/03091900110043621

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


  12 in total

1.  Analysis of breast thermograms using Gabor wavelet anisotropy index.

Authors:  S S Suganthi; S Ramakrishnan
Journal:  J Med Syst       Date:  2014-07-27       Impact factor: 4.460

2.  Thermal distribution analysis of three-dimensional tumor-embedded breast models with different breast density compositions.

Authors:  Asnida Abd Wahab; Maheza Irna Mohamad Salim; Mohamad Asmidzam Ahamat; Noraida Abd Manaf; Jasmy Yunus; Khin Wee Lai
Journal:  Med Biol Eng Comput       Date:  2015-10-13       Impact factor: 2.602

Review 3.  Comparison of standard mammography with digital mammography and digital infrared thermal imaging for breast cancer screening.

Authors:  Nermin Köşüş; Aydın Köşüş; Müzeyyen Duran; Serap Simavlı; Nilgün Turhan
Journal:  J Turk Ger Gynecol Assoc       Date:  2010-09-01

4.  A Model for Diagnosing Breast Cancerous Tissue from Thermal Images Using Active Contour and Lyapunov Exponent.

Authors:  Hossein Ghayoumi Zadeh; Javad Haddadnia; Alimohammad Montazeri
Journal:  Iran J Public Health       Date:  2016-05       Impact factor: 1.429

5.  Parameter estimation of breast tumour using dynamic neural network from thermal pattern.

Authors:  Elham Saniei; Saeed Setayeshi; Mohammad Esmaeil Akbari; Mitra Navid
Journal:  J Adv Res       Date:  2016-06-03       Impact factor: 10.479

Review 6.  Application of infrared thermography in computer aided diagnosis.

Authors:  Oliver Faust; U Rajendra Acharya; E Y K Ng; Tan Jen Hong; Wenwei Yu
Journal:  Infrared Phys Technol       Date:  2014-06-20       Impact factor: 2.638

7.  Millikelvin-resolved ambient thermography.

Authors:  Kechao Tang; Kaichen Dong; Christopher J Nicolai; Ying Li; Jiachen Li; Shuai Lou; Cheng-Wei Qiu; David H Raulet; Jie Yao; Junqiao Wu
Journal:  Sci Adv       Date:  2020-12-09       Impact factor: 14.136

8.  Correlation between Isotherms and Isodoses in Breast Cancer Radiotherapy-First Study.

Authors:  Dominika Plaza; Agnieszka Baic; Barbara Lange; Agata Stanek; Krzysztof Ślosarek; Anna Kowalczyk; Armand Cholewka
Journal:  Int J Environ Res Public Health       Date:  2021-01-13       Impact factor: 3.390

9.  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

Review 10.  Medical applications of infrared thermography: A review.

Authors:  B B Lahiri; S Bagavathiappan; T Jayakumar; John Philip
Journal:  Infrared Phys Technol       Date:  2012-04-13       Impact factor: 2.638

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