The Effect of Thermography on Breast Cancer Detection-A Survey

Pavithra, P; Ks, Ravichandran; Sekar, KR; Manikandan, Ramaswamy

doi:10.5530/srp.2018.1.3

Cited by 31 publications

(15 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The a 1 parameter is calculated by Eq. 2 in step (7). The position of leading salp is changed by Eq.…”

Section: B Salp Swarm Algorithm (Ssa)mentioning

confidence: 99%

“…In thermal imaging, patterns for the body are recorded without emitting any radiation by using a functional image rather than the structural image. It depends on increasing the temperature of the breast surface to determine if the breast cells are healthy or not [7]. The most common type of datasets, in research, is the dataset for Mastology Research with Infrared Image [8], [9].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Breast Cancer Segmentation From Thermal Images Based on Chaotic Salp Swarm Algorithm

et al. 2020

View full text Add to dashboard Cite

Breast cancer is one of the most common types of cancer and early detection can significantly decrease the associated mortality rate. Different kinds of segmentation methods were applied to extract regions of interest from breast cancer images that are necessary to improve the classification. In this paper, a segmentation method for breast cancer from thermal images is introduced based on a proposed Chaotic Salp Swarm Algorithm (CSSA). Although the Salp Swarm Algorithm (SSA) shows superiority in singleobjective optimization problems, it suffers from a low convergence rate and local optima stagnation. In the proposed method, a segmentation algorithm is formulated using the quick-shift method for superpixels extraction whose parameters are optimized by CSSA. The quick-shift method generates compact and nearly uniform superpixels by clustering the breast thermal image pixels. CSSA algorithm is developed based on ten chaotic maps to enhance the original SSA convergence rate while accuracy could be improved by controlling the balance between exploration and exploitation. The proposed algorithm is applied to realworld thermal images for the breast area. The results demonstrate that the proposed CSSA algorithm achieves fast convergence for the unimodal benchmark functions and outperforms the original SSA algorithm. Moreover, a dataset from Mastology Research with Infrared Image (DMR-IR) is used to test the performance of the proposed algorithm. In experiments, the proposed optimized segmentation algorithm extracts the breast area from the background accurately where the region of interest is focused on the breast area and removes the unwanted area such as underarms and stomach which intern can enhance the results of cancer detection. Furthermore, the proposed algorithms achieve robustness for the segmentation of different healthy and unhealthy cases images compared to the state-of-the-art methods.

show abstract

“…The a 1 parameter is calculated by Eq. 2 in step (7). The position of leading salp is changed by Eq.…”

Section: B Salp Swarm Algorithm (Ssa)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Breast Cancer Segmentation From Thermal Images Based on Chaotic Salp Swarm Algorithm

et al. 2020

View full text Add to dashboard Cite

show abstract

“…In this regard, having a more exact identification of bleeding point by means of contrast-enhanced computed tomography (CECT) scan has effectively improved the detection process of symptom identification and strengthened the productiveness of interventional radiology (IR). Consequently, immediate access to these two introduced imaging techniques is one of the most important steps in achieving further development and innovation in trauma care systems [69,70].…”

Section: The Novel System Of Hybrid Emergency Roommentioning

confidence: 99%

A Review of Assessment and Treatment of Trauma in Emergency Department

2020

jcr

View full text Add to dashboard Cite

Background:Traumatic injuries are the major destructive causes of human disability and in some situations, they could cause mortality. Preparing an appropriate procedure for the management and treatment of trauma patients is still a big challenge. Anyway, through immediate diagnosis and management of trauma patients in emergency departments mainly in trauma golden hour most appropriate outcomes could be achieved. The initial examination of trauma patients should be carried out in the trauma golden hour by most appropriate diagnosis equipment prepared in the emergency trauma care unit. Objective:The present study was performed for reviewing the most appropriate techniques and equipment of diagnosis and management of traumatic injuries. Material and Method:For obtaining the most appropriate outcomes, a comprehensive review carried out through the general medical databases of PubMed, Embase, Google Scholar, MEDLINE, databases of Cochrane Library, Allied and Complementary Medicine Database and Allied Health Literature of CINAHL on care system of patients who suffer from various kinds of trauma were searched up to March 2020. Finally, the total number of 73 articles were selected for reviewing the newest available data around the main objective of the present study. Results:Trauma patients who detected with serious injuries in their vital organs should be managed through an appropriate standardized guideline. This comprehensive guideline is categorized into fourteen critical steps that provide general information about the importance, objective, initial actions, required equipment and staff and also the overall knowledge of any step in diagnosis and management of trauma patients. Conclusion:The prepared comprehensive guideline for appropriate management of trauma patients is a precise effective method for immediate management of trauma patients in trauma care units of emergency departments. The most critical situation such as severely injured patients, airway management, protecting breathing and circulation, major neurologic problems and the difficulties with clinical examination of whole-body could be managed through following the prepared guideline.

show abstract

“…Thermal spread in biological tissue may be measured using an infrared thermograph device [5]. Images of surface temperature and false-positive and false-negative constitute limitations of the infrared thermography method [6,7]. Therefore, several researchers have addressed their efforts to know how the temperature is distributed in a tissue (i.e., the tumor) [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Analytical solution of the bioheat equation for thermal response induced by any electrode array in anisotropic tissues with arbitrary shapes containing multiple-tumor nodules

Oria¹,

Cabrales

Reyes

2019

Rev. Mex. Fís.

View full text Add to dashboard Cite

The Pennes bioheat transfer equation is the most used model to calculate the temperature induced in a tumor when physical therapies like electrochemical treatment, electrochemotherapy and/or radiofrequency are applied. In this work, a modification of the Pennes bioheat equation to study the temperature distribution induced by any electrode array in an anisotropic tissue containing several nodules (primary or metastatic) with arbitrary shape is proposed. For this, the Green functions approach is generalized to include boundaries among two or more media. The analytical solution we obtain in a very compact way, under quite general suppositions, allows calculating the temperature distributions in the tumor volumes and their surfaces, in terms of heat sources, initial temperature and calorific sources at the boundary of tumors.

show abstract

The Effect of Thermography on Breast Cancer Detection-A Survey

Cited by 31 publications

References 33 publications

Breast Cancer Segmentation From Thermal Images Based on Chaotic Salp Swarm Algorithm

Breast Cancer Segmentation From Thermal Images Based on Chaotic Salp Swarm Algorithm

A Review of Assessment and Treatment of Trauma in Emergency Department

Analytical solution of the bioheat equation for thermal response induced by any electrode array in anisotropic tissues with arbitrary shapes containing multiple-tumor nodules

Contact Info

Product

Resources

About