A Novel Tactile Sensor for Detecting Lumps in Breast Tissue

Ayyıldız, Mehmet; Güçlü, Burak; Yıldız, Mustafa Zahid; Başdoğan, Çağatay

doi:10.1007/978-3-642-14064-8_53

Cited by 5 publications

(3 citation statements)

References 9 publications

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“…In this paper, we present a novel optoelectromechanical TI system, which can be utilized to guide the clinician or the self-user at home for noninvasive detection of tumors in breast tissue [36]. In our design, an array of optical elements consisting of an integrated IR emitting diode and a photodarlington transistor were used as sensors.…”

Section: Discussionmentioning

confidence: 99%

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An Optoelectromechanical Tactile Sensor for Detection of Breast Lumps

Ayyıldız

Güçlü

Yıldız

et al. 2013

IEEE Trans. Haptics

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We developed a compact tactile imaging (TI) system to guide the clinician or the self-user for noninvasive detection of breast tumors. Our system measures the force distribution based on the difference in stiffness between a palpated object and an abnormality within. The average force resolution, force range, and the spatial resolution of the device are 0.02 N, 0-4 N, and 2.8 mm, respectively. To evaluate the performance of the proposed TI system, compression experiments were performed to measure the sensitivity and specificity of the system in detecting tumor-like inclusions embedded in tissue-like cylindrical silicon samples. Based on the experiments performed with 11 inclusions, having two different sizes and two different stiffnesses located at three different depths, our TI system showed an average sensitivity of 90.8 ± 8.1 percent and an average specificity of 89.8 ± 12.7 percent. Finally, manual palpation experiments were performed with 12 human subjects on the same silicon samples and the results were compared to that of the TI system. The performance of the TI system was significantly better than that of the human subjects in detecting deep inclusions while the human subjects performed slightly better in detecting shallow inclusions close to the contact surface.

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Section: Discussionmentioning

confidence: 99%

“…The silicone samples containing an inclusion were compressed to the depths of 15 and 19 mm. These depths were selected based on the results of our earlier study [36]. For each depth, the compression experiment was repeated 20 times on each silicon sample.…”

Section: Compression Experimentsmentioning

confidence: 99%

An Optoelectromechanical Tactile Sensor for Detection of Breast Lumps

Ayyıldız

Güçlü

Yıldız

et al. 2013

IEEE Trans. Haptics

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“…This behavior has led researchers to focus on building a device that uses tactile sensors and touch the patient's breast tissue to quantify its stiffness and use the results to identify cancer masses. Although this method has been used to identify and treat some other diseases [5,6], but its main application is in identifying breast cancer masses. In many early studies conducted by researchers, measuring the modulus of elasticity of breast tissue and analyzing its changes is the basis for identifying cancer masses.…”

Section: Introductionmentioning

confidence: 99%

Diagnosing Soft Tissue Sub-Surface Masses Using the XCS Classification System

Yazdani¹

2020

Front Health Inform

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Introduction: One of the most common types of cancer is breast cancer, which is considered as the second leading cause of death in women in Iran. Due to the fatality of this type of cancer, it is very important to diagnose the disease in the early stages and starting the treatment process. One of the methods to diagnose breast cancer is using mechanical arms (robot manipulator) to touch and measure the force in terms of displacement at the site of the breast touch by the robot. The hardness of the cancer tissue can affect the force diagram in terms of displacement, which can be used as a diagnostic method. The present study was performed to prepare a simulation model of breast soft tissue behavior considering subsurface masses. Then, a proposed classification system was designed to fit it.Material and Methods: In this section, first, the soft tissue behavior of the breast is simulated by considering sub-surface masses. The simulations are performed for a piece of tissue that is in the shape of a rectangular cube, as well as different dimensions of a spherical mass that is located at different depths and coordinates. Using simulation, various force-displacement diagrams have been obtained, based on which a data network.Results: The displacement force diagram for different modes is obtained using simulation. By giving the resulting diagrams to the trained system, the size and depth of the mass is determined. By comparing the obtained results with the initial model and the actual size and depth of the mass, a very good conformity is observed, which indicates the correct operation of the designed system and the performed simulation process.Conclusion: The proposed design system was used to diagnose the presence of tumors in tissue with sub-surface mass. The results show a high percentage of this method in diagnosis. However, the accuracy of this method can be greatly increased by increasing the amount of data given to the XCS system for training. On the other hand, instead of simulation data, test data on healthy and unhealthy people can be used for training.

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