Breast abnormality detection through statistical feature analysis using infrared thermograms

Gogoi, Usha Rani; Majumdar, G.; Bhowmik, Mrinal Kanti; Ghosh, Anjan; Bhattacharjee, Debotosh

doi:10.1109/isacc.2015.7377351

Cited by 50 publications

(9 citation statements)

References 25 publications

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“…It should also be noted that the condition confirming the lack of thermal asymmetry based on the interpretation standards established for thermal imaging examinations is the result of the individual assessment of the value of temperature differences for contralateral areas of the body, not exceeding the value up to 0.5 • C. It should also be noted that the condition confirming the lack of thermal asymmetry based on interpretation standards established for thermal imaging examinations is the result of the individual assessment of the value of temperature differences for contralateral areas of the body, not exceeding the value up to 0.5 • C. Despite the lack of significant differences in the mathematical statistical analysis, our research showed that the individual differences in the mean values of right and left breast temperatures often exceed this value up to the maximum thermal difference of 1.4 • C for the entire breast and 1.5 • C for the nipple area, which is probably conditioned by the blood supply to the mammary glands and the high variability of individual metabolism, which does not necessarily indicate pathological changes. It is reported in the literature that the thermograms that have slight asymmetric temperature distributions signify the physiological dysfunction in patients' breasts in most cases [19][20][21], but usually in individuals with non-tumorous breasts, the surface temperature of both breasts is close to symmetric. When there is a tumor or an abnormality, such as fibrosis, inflammation, infection, or benign condition, the symmetry is lost, and the surface temperature is altered in response to more metabolically active tumors than healthy tissue, formation of new blood vessels (angiogenesis) to sustain their accelerated growth, and growth of a more robust blood flow network [22].…”

Section: Discussionmentioning

confidence: 99%

Thermal Characteristics of Breast Surface Temperature in Healthy Women

Lubkowska

Chudecka

2021

IJERPH

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Thermography is widely used in the medical field, including in the detection of breast disorders. The aim of the research was to characterize the range of breast surface temperature values, taking into account the entire area of the mammary gland and, independently, the nipple, in healthy women. An additional aim was to assess the symmetry of the breast temperature distribution (using an IR camera) and the correlation of temperatures with the content of adipose tissue. Thermograms were made for the right and left breasts, each time delineating the area of the entire breast and a separate area of the nipple, chest, and abdomen. Analyzing the intergroup differences in temperature of selected body areas (Tmean), it was shown that, in all cases, they were significantly higher in younger women. Statistical analysis showed no significant differences between breast and nipple temperatures in relation to the body sides. The highest temperatures within the mammary gland were recorded for the nipple area. The use of the high-resolution digital infrared thermal imaging method in early and screening preventive diagnoses of changes in the mammary gland requires individual interpretation of the results, taking into account the assessment of the physiological pattern of temperature distribution in both breasts.

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Section: Discussionmentioning

confidence: 99%

Thermal Characteristics of Breast Surface Temperature in Healthy Women

Lubkowska

Chudecka

2021

IJERPH

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“…On the other hand, the DMR-IR database has been used to evaluate the efficiency of the most common extracted features such as texture [19,[28][29][30][31], shape [32], and morphology [33] descriptors to classify thermal patterns. However, the discriminative power of the physiological descriptors has not been evaluated on the above-mentioned database.…”

Section: Discussionmentioning

confidence: 99%

Highly Discriminative Physiological Parameters for Thermal Pattern Classification

Alvarado-Cruz

Toxqui-Quitl

Castro-Ortega

et al. 2021

Sensors

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Infrared Thermography (IRT) is a non-contact, non-intrusive, and non-ionizing radiation tool used for detecting breast lesions. This paper analyzes the surface temperature distribution (STD) on an optimal Region of Interest (RoI) for extraction of suitable internal heat source parameters. The physiological parameters are estimated through the inverse solution of the bio-heat equation and the STD of suspicious areas related to the hottest spots of the RoI. To reach these values, the STD is analyzed by means: the Depth-Intensity-Radius (D-I-R) measurement model and the fitting method of Lorentz curve. A highly discriminative pattern vector composed of the extracted physiological parameters is proposed to classify normal and abnormal breast thermograms. A well-defined RoI is delimited at a radial distance, determined by the Support Vector Machines (SVM). Nevertheless, this distance is less than or equal to 1.8 cm due to the maximum temperature location close to the boundary image. The methodology is applied to 87 breast thermograms that belong to the Database for Mastology Research with Infrared Image (DMR-IR). This methodology does not apply any image enhancements or normalization of input data. At an optimal position, the three-dimensional scattergrams show a correct separation between normal and abnormal thermograms. In other cases, the feature vectors are highly correlated. According to our experimental results, the proposed pattern vector extracted at optimal position a=1.6 cm reaches the highest sensitivity, specificity, and accuracy. Even more, the proposed technique utilizes a reduced number of physiological parameters to obtain a Correct Rate Classification (CRC) of 100%. The precision assessment confirms the performance superiority of the proposed method compared with other techniques for the breast thermogram classification of the DMR-IR.

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“…There are a number of research works on breast cancer detection using thermography in recent times. Gogoi et al [ 1 ] used the statistical features, to detect abnormal breasts from normal ones in thermograms, while most of the works used the statistical features of thermograms for finding the asymmetry between the two breasts. In this paper, the Gabor features are used to capture the textural differences between the two asymmetric breasts.…”

Section: Literature Reviewmentioning

confidence: 99%

Thermography as an Economical Alternative Modality to Mammography for Early Detection of Breast Cancer

Khan

Arora

2021

Journal of Healthcare Engineering

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Breast cancer has become a menacing form of cancer among women accounting for 11.6% of total deaths of 9.6 million due to all types of cancer every year all over the world. Early detection increases chances of survival and reduces the cost of treatment as well. Screening modalities such as mammography or thermography are used to detect cancer early; thus, several lives can be saved with timely treatment. But, there are interpretational failures on the part of the radiologists to read the mammograms or thermograms and also there are interobservational and intraobservational differences between them. So, the degree of variations among the different radiologists in the interpretation of results is very high resulting in false positives and false negatives. The double reading can reduce the human errors involved in the interpretation of mammograms. But, the limited number of medical professionals in developing or underdeveloped countries puts a limitation on this remedial way. So, a computer-aided system (CAD) is proposed to detect the benign cases from the abnormal cases that can result in automatic detection of breast cancer or can provide a double reading in the case of nonavailability of the trained medical professionals in developing economies. The generally accepted screening modality is mammography for the early detection of cancer. But thermography has been tried for early detection of breast cancer in recent times. The high metabolic activity of the cancer cells results in an early change in the temperature profile of the region. This shows asymmetry between normal and cancerous breast which can be detected using different techniques. Thus, this work is focussed on the use of thermography in the early detection of breast cancer. An experimental study is conducted to find the results of classification accuracy to compare the efficacy of thermography and mammography in classifying the normal from abnormal ones and further abnormal ones into benign and malignant cases. Thermography is found to have classification accuracy almost at par with mammography for classifying the cancerous breasts from healthy ones with classification accuracies of thermography and mammography being 96.57% and 98.11%, respectively. Thermography is found to have much better accuracy in identifying benign cases from the malignant ones with the classification accuracy of 92.70% as compared to 82.05% with mammography. This will result in the early detection of cancer. The advantage of being portable and inexpensive makes thermography an attractive modality to be used in economically backward rural areas where mammography is not practically possible.

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Breast abnormality detection through statistical feature analysis using infrared thermograms

Cited by 50 publications

References 25 publications

Thermal Characteristics of Breast Surface Temperature in Healthy Women

Thermal Characteristics of Breast Surface Temperature in Healthy Women

Highly Discriminative Physiological Parameters for Thermal Pattern Classification

Thermography as an Economical Alternative Modality to Mammography for Early Detection of Breast Cancer

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