A Computational Method to Assist the Diagnosis of Breast Disease Using Dynamic Thermography

Silva, Thiago Alves Elias da; Silva, Lincoln Faria da; Muchaluat-Saade, Débora C.; Conci, Aura

doi:10.3390/s20143866

Cited by 30 publications

(26 citation statements)

References 31 publications

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“…It has been used for mass screening of people in other pandemics such as H1N1 and Ebola so it can be applied in this current pandemic of COVID-19 [ 92 ]. Thermography works by using infrared radiation to calculate the temperature of the human body [ 93 ]. Abnormal body temperatures are a well-known indication of infection [ 94 ].…”

Section: Non-contact Sensing To Detect Covid-19 Symptomsmentioning

confidence: 99%

A Review of the State of the Art in Non-Contact Sensing for COVID-19

Taylor

Abbasi

Dashtipour

et al. 2020

Sensors

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COVID-19, caused by SARS-CoV-2, has resulted in a global pandemic recently. With no approved vaccination or treatment, governments around the world have issued guidance to their citizens to remain at home in efforts to control the spread of the disease. The goal of controlling the spread of the virus is to prevent strain on hospitals. In this paper, we focus on how non-invasive methods are being used to detect COVID-19 and assist healthcare workers in caring for COVID-19 patients. Early detection of COVID-19 can allow for early isolation to prevent further spread. This study outlines the advantages and disadvantages and a breakdown of the methods applied in the current state-of-the-art approaches. In addition, the paper highlights some future research directions, which need to be explored further to produce innovative technologies to control this pandemic.

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Section: Non-contact Sensing To Detect Covid-19 Symptomsmentioning

confidence: 99%

A Review of the State of the Art in Non-Contact Sensing for COVID-19

Taylor

Abbasi

Dashtipour

et al. 2020

Sensors

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“…Simulations considering no skin ventilation and superficial cooling and reheating were performed [28]. For the cooling period, a thermal perturbation over the neck surface with electric fan airflow was simulated [17, 30]. The reheating period is based on the return to thermal equilibrium with the environment (the examination room) immediately after the cooling period.…”

Section: Methodsmentioning

confidence: 99%

“…Digital Infrared Thermal Imaging (DITI) [14] is a non-invasive technique based on IRT that allows us to visualize and quantify temperature changes in the skin surface [15]. DITI has been successfully explored in various fields of medicine, such as the determination of circulatory problems, assessment of the body's reaction to a medication, physiotherapy treatments, study and diagnosis of various conditions, and detection of various cancers, especially breast tumors [15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

A computational study on the role of parameters for identification of thyroid nodules by infrared images (and its comparison with real data)

Montero

Damiao

Moran

et al. 2021

Preprint

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According to experts and medical literature, a healthy thyroid gland, or a thyroid containing benign nodules, tend to be less inflamed and less active than one with malignant nodules. It seems to be a consensus that malignant nodules have more blood veins and it may be related to the maintenance of high and constant temperatures. Investigation of these characteristics, detectable by infrared sensors, and answering if they constitute patterns of malignancy are the aims of this work. Experiments considering biological heat transfer analysis by Finite Element numerical simulations are used to show the influence of nodule and patient characteristics on the identification of malignancy of thyroid nodule by thermography. The used and approved protocol for infrared examination are analyzed and simulated during all its phase that is on transient and steady state behavior, in order to verify how and when their influence can be really recognized in patients. Simulation results and the analysis of infrared exams show that the tissues between the skin and the thyroid, as well as the nodule size, have influence in superficial temperatures. Other thermal parameters of thyroid nodules are also investigated and show little influence on surface temperatures. These characteristics must be considered in nodular infrared analysis and diagnosis by thermography. The infrared examinations of patients that meet the hypotheses related to the vascularization of the nodule confirm the numerical results. All details of the physical parameters used in the simulations, characteristics of the nodules, and their complete thermal examinations are public and available, turning possible that the presented simulation could be compared with other types of heat transfer solutions. This study is a concrete contribution to the answer of under what conditions thermography can be useful in the identification of thyroid nodules.Author summaryThyroid nodules are very common health problems. These nodules may have different characteristics, and some of them could influence the temperature of the region. Many works in the medical literature report that the healthy thyroid and even benign nodules tend to be less inflamed and active than malignant nodules and therefore should exhibit some variation in patterns of behavior related to the temperature variation between them. The focus of this work is to analyze some parameters of the nodules and details of the patients that can influence the identification and diagnosis of thyroid nodules by infrared images. To reach the objective, simulations of bioheat transfer in the neck (using a simple neck geometry and Finite Elements Analysis in COMSOL Multiphysics Software) and real infrared examinations (performed with a FLIR Infrared Camera model SC620 and a proposed protocol) were analyzed. Our results show the thermal insulation effect of the neck fat tissue, and that the effect of nodule sizes can be decremented by a thicker layer of fat. The analysis of the nodule parameters as blood perfusion rate and metabolic heat, which could be related with the nodule vascularization (an important condition related with malignancy), suggest that the thermal effects of thyroid nodules on the neck surface are not sufficient to differentiate benign from malign, and for this other features or methods must be considered.

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“…Some researchers have used the bottleneck features of these pretrained CNNs to train traditional classifiers, including support vector machine (SVM), knearest neighbors (KNN), logistic regression (LR), and decision trees, which can take full advantage of the implicit characteristics of the traditional classifiers. For example, Silva et al [15] trained an SVM-based classifier for breast disease diagnosis. Cong et al [16] proposed an ensemblelearning method that integrates a group of traditional classifiers, including KNN, SVM, and naive Bayes, to complete breast cancer recognition.…”

Section: A Breast Cancer Recognitionmentioning

confidence: 99%

Effective Breast Cancer Recognition Based on Fine-Grained Feature Selection

Yuan

et al. 2020

IEEE Access

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A Computational Method to Assist the Diagnosis of Breast Disease Using Dynamic Thermography

Cited by 30 publications

References 31 publications

A Review of the State of the Art in Non-Contact Sensing for COVID-19

A Review of the State of the Art in Non-Contact Sensing for COVID-19

A computational study on the role of parameters for identification of thyroid nodules by infrared images (and its comparison with real data)

Effective Breast Cancer Recognition Based on Fine-Grained Feature Selection

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