Interpolation in imaging is defined as:

Interpolation in imaging is defined as:

• A. Direct measurement at every point
• B. A method using known data to estimate values at unknown points
• C. A process of interpolation is not used in OCT
• D. Random guessing between data points

Answer: (B)

Interpolation is the process of estimating unknown values between known samples by using the information from nearby data. In OCT imaging, signals are collected at discrete locations (for example along depth or across a cross-section). To create a smooth image or to resample data onto a common grid, we estimate the values at points where no measurement exists, based on the surrounding measured points. This approach is a purposeful estimate, not an extra measurement and not random guessing, and it’s commonly done with methods ranging from simple linear interpolation to more advanced cubic or spline techniques. So, the idea that interpolation uses known data to estimate values at unknown points is the correct one.

Interpolation is the process of estimating unknown values between known samples by using the information from nearby data. In OCT imaging, signals are collected at discrete locations (for example along depth or across a cross-section). To create a smooth image or to resample data onto a common grid, we estimate the values at points where no measurement exists, based on the surrounding measured points. This approach is a purposeful estimate, not an extra measurement and not random guessing, and it’s commonly done with methods ranging from simple linear interpolation to more advanced cubic or spline techniques. So, the idea that interpolation uses known data to estimate values at unknown points is the correct one.