Department of Electrical and Instrumentation, Sant Longowal Institute of Engineering and Technology, Longowal 148106, India.
J Healthc Eng. 2021 Jul 31;2021:5543101. doi: 10.1155/2021/5543101. eCollection 2021.
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.
乳腺癌已成为全球每年因各种癌症导致的 960 万总死亡人数中占 11.6%的女性的一种威胁性癌症。早期发现可以提高生存机会并降低治疗成本。乳腺摄影术或热成像术等筛查方式用于早期发现癌症;因此,及时治疗可以挽救几条生命。但是,放射科医生在阅读乳腺 X 光片或热图像时存在解释错误,并且他们之间存在观测和内部观测差异。因此,不同放射科医生在解释结果时的变异程度非常高,导致假阳性和假阴性。双读可以减少乳腺 X 光片解释中的人为错误。但是,发展中国家和不发达国家的医疗专业人员数量有限,限制了这种补救方法。因此,提出了一种计算机辅助系统 (CAD),用于从异常病例中检测良性病例,从而可以自动检测乳腺癌,或者在发展中经济体中没有受过培训的医疗专业人员的情况下提供双读。普遍接受的筛查方式是乳腺 X 光检查,用于早期发现癌症。但是,近年来已经尝试使用热成像术早期发现乳腺癌。癌细胞的高代谢活性导致该区域的温度曲线早期发生变化。这显示了正常和癌变乳房之间的不对称性,可以使用不同的技术进行检测。因此,这项工作专注于热成像术在早期检测乳腺癌中的应用。进行了一项实验研究,以找到分类准确性的结果,以比较热成像术和乳腺 X 光检查在将正常和异常病例分类为良性和恶性病例方面的效果。发现热成像术在将癌症乳房与健康乳房分类方面的分类准确性几乎与乳腺 X 光检查相当,热成像术和乳腺 X 光检查的分类准确性分别为 96.57%和 98.11%。发现热成像术在识别良性病例和恶性病例方面的准确性要高得多,分类准确性为 92.70%,而乳腺 X 光检查的分类准确性为 82.05%。这将导致癌症的早期发现。便携性和价格低廉的优势使热成像术成为一种有吸引力的模式,可用于经济落后的农村地区,在这些地区实际上不可能进行乳腺 X 光检查。