Abstract

Soft tissues are non-homogeneous deformable structures having varied structural arrangements, constituents, and composition. This chapter explains the design of a capacitance sensor array for analyzing and imaging the non-homogeneity in biological materials. Further, tissue mimicking phantoms are developed using Agar-Agar and Polyacrylamide gels for testing the developed sensor. Also, the sensor employs an unsupervised learning algorithm for automated analysis of non-homogeneity. The reconstructed capacitance image can also be sensitive to topographical and morphological variations in the sample. The proposed method is further validated using a fiberoptic-based laser imaging system and the Jaccard index. In this chapter, the design of the sensor array for smart analysis of non-homogeneity along with significant results are presented in detail.

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