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计算机乳腺热成像:图像分割与温度周期性变化研究

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

作者信息

Ng E Y, Chen Y, Ung L N

机构信息

School of Mechanical and Production Engineering, Nanyang Technological University, Singapore.

出版信息

J Med Eng Technol. 2001 Jan-Feb;25(1):12-6. doi: 10.1080/03091900010022247.


DOI:10.1080/03091900010022247
PMID:11345095
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.

摘要

乳腺癌是女性常见且可怕的疾病。乳房的表面温度和血管分布模式可能预示着乳房疾病。建立乳房的表面等温线模式以及温度分布的周期性变化正常范围,有助于识别患病乳房的异常红外图像。本文研究了在可控环境下正常乳房热成像图的温度和血管分布的周期性变化。对50多名亚洲女性进行了检查,其中一些人连续检查了两个月。总共获得了不少于800张热成像图。在通过计算机算法对这些热成像图进行客观分析之前,必须先将其数字化并进行分割。作者提出了一种分割热成像图并从背景中提取有用区域的方法。经过图像处理后,就可以对这些热成像图进行分析,进而选择最佳的检查时间。所有这些结果对于建立正常乳房热成像数据库、选择最佳检查时间以及作为未来评估和分析异常乳房热成像的系统方法都很重要。

相似文献

[1]
Computerized breast thermography: study of image segmentation and temperature cyclic variations.

J Med Eng Technol. 2001

[2]
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[3]
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[4]
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[5]
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[6]
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[7]
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引用本文的文献

[1]
Risk of breast cancer based on thermal tomography characteristics.

Transl Cancer Res. 2019-8

[2]
Application of infrared thermography in computer aided diagnosis.

Infrared Phys Technol. 2014-9

[3]
Supportive Noninvasive Tool for the Diagnosis of Breast Cancer Using a Thermographic Camera as Sensor.

Sensors (Basel). 2017-3-3

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

EXCLI J. 2016-8-26

[5]
Thermography based breast cancer detection using texture features and minimum variance quantization.

EXCLI J. 2014-11-4

[6]
Level set method for segmentation of infrared breast thermograms.

EXCLI J. 2014-3-13

[7]
Mechanisms of Laser-Tissue Interaction: II. Tissue Thermal Properties.

J Lasers Med Sci. 2013

[8]
Intelligent neonatal monitoring based on a virtual thermal sensor.

BMC Med Imaging. 2014-3-2

[9]
Evaluation of the diagnostic power of thermography in breast cancer using Bayesian network classifiers.

Comput Math Methods Med. 2013-5-22

[10]
Breast imaging: A survey.

World J Clin Oncol. 2011-4-10

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