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Early detection is the most important strategy for controlling and management of cancer, which can significantly increase the survival rate by detecting disease in the early stages and rapid treating and preventing the progression of the disease. Based on existence of specific cell frequencies in the form of the response of each cell to its own specific frequency and the difference between normal and tumor cell frequency levels as a hallmark for cancer detection, we suggest using Graphene-based metasurfaces. Owing to the outstanding physical properties of graphene, its biosensing applications implemented by the terahertz metasurface are widely concerned and studied.a novel design of the graphene metasurface, proposed by ( Tan et al., 12) consists of an individual graphene ring and an Hshaped graphene structure. The graphene metasurface exhibits a dual-resonance response, whose resonance frequency strongly varies with its geometrical parameters. The simulated results clearly show that the theoretical sensitivity, figure of merit, and quantity of the proposed graphene metasurface for breast cells reach 1.21 THz/RIU, 2.75 RIU-1, and 2.43, respectively. These findings may open up new avenues for promising applications in the diagnosis of cancers.

Human sperm motility is of great interest to researchers and biologists studying sperm function and to medical practitioners evaluating and treating male in-fertility. Computer-assisted semen analysis (CASA) instruments are used to trace the swimming paths of sperm automatically in time-lapse microscopy image sequences connect-the-dots between video frames, enabling rapid automatic quantification of sperm motility parameters for hundreds of cells at a time. The image processing and sperm tracking capabilities of today’s CASA instruments can be enhanced However. In this paper we highlighted the limitations of (CASA) instruments and suggested ways to mitigate them from the literature. We have also our algorithm ‒ program complex to determine linear velocity in Java. With all these efforts in further improving the computational tools for CASA, much more robust and versatile systems should be available in the foreseeable future.