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Soft tissue abnormalities are often correlated with a change in the mechanical properties of the soft tissue. New developing non-invasive techniques with the ability of early detection of cancerous tissue with high accuracy is a challenging state of art. In this paper, a new method is proposed to investigate the liver tissue cancers. Hyperelastic behavior of a porcine liver tissue has been extracted from the in vitro stress-strain experimental tests of the tissue. Hyperelastic coefficients have been used as the input of the Abaqus FEM software and the palpation of a physician has been simulated. The soft tissue contains a tumor with specified mechanical and geometrical properties. Artificial tactile sensing capability in tumor detection and localization has been investigated thoroughly. In mass localization we have focused on deeply located tumor which is a challenging area in the medical diagnosis. Moreover, tumor type differentiation which is commonly achieved through pathological investigations is studied by changing the stiffness ratio of the tumor and the tissue. Results show that the new proposed method has a high ability in mass detection, localization and type differentiation.

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Soft tissue’s cancers are related to major variations in the mechanical properties of the tissue. In recent years, a number of developing techniques have been introduced for early detection of soft tissue’s cancers. The major advantage of these methods over the common available techniques is while being noninvasive to the body, the accuracy of detection is noticeably increased. This article intends to analyze mechanical behavior of the breast tissue by considering a Mooney-Rivlin hyperelastic model. Coefficients of the model are defined by using a series of experimental mechanical datasets. For this purpose, a mechanical device is designed and fabricated base on a new noninvasive method named Artificial Tactile Sensing (ATS). The device is examined on 8 patients in 20 to 50 age range refer to “Jahad Daneshgahi Breast Diseases Clinic” while considering Helsinki agreement’s protocols. Due to wide anatomical variations of the breast tissue in individuals, 40 specified regions are examined on the tissues of all attended cases. Experimental stress versus strain datasets are collected for 40 test points. To achieve a reliable and optimized model, a genetic algorithm (GA) is used for calculating Mooney-Rivlin’s coefficients. Results confirmed that an accurate model can be afforded to estimate the soft tissue’s mechanical behavior with the least error. The model is suitable for disease diagnosis and follow-up procedure.