This paper compares the performance of Fourier Domain Optical Coherence Tomography (FDOCT) with Time Domain OCT (TDOCT). It discusses noise sources in FDOCT systems and confirms that FDOCT has a significant sensitivity advantage, achieving sensitivities above 80 dB even in low light conditions and high-speed detection. FDOCT measures optical energy rather than power, using CCD detectors to collect photoelectron charges during exposure time. The interference pattern is recorded by a spectrometer as a function of frequency, and the object structure is obtained via a discrete Fourier transform (DFT). The paper analyzes noise sources, including shot noise, excess noise, receiver noise, and 1/f noise, and shows that FDOCT's noise rms is reduced by a factor of √N due to DFT processing. The signal-to-noise ratio (SNR) is defined as the ratio of the OCT signal to noise, and the sensitivity of FDOCT is calculated based on the minimum sample arm reflectivity for which the SNR equals one. The sensitivity of FDOCT is found to be higher than TDOCT, especially in low light conditions. The paper also discusses the effects of DFT on signal amplitude and noise, and the importance of minimizing exposure time and subtracting reference arm signals to reduce coherent noise. The results show that FDOCT has a significant advantage in sensitivity and is suitable for low light situations such as high-speed imaging. The paper concludes that FDOCT is the preferred method for such applications.This paper compares the performance of Fourier Domain Optical Coherence Tomography (FDOCT) with Time Domain OCT (TDOCT). It discusses noise sources in FDOCT systems and confirms that FDOCT has a significant sensitivity advantage, achieving sensitivities above 80 dB even in low light conditions and high-speed detection. FDOCT measures optical energy rather than power, using CCD detectors to collect photoelectron charges during exposure time. The interference pattern is recorded by a spectrometer as a function of frequency, and the object structure is obtained via a discrete Fourier transform (DFT). The paper analyzes noise sources, including shot noise, excess noise, receiver noise, and 1/f noise, and shows that FDOCT's noise rms is reduced by a factor of √N due to DFT processing. The signal-to-noise ratio (SNR) is defined as the ratio of the OCT signal to noise, and the sensitivity of FDOCT is calculated based on the minimum sample arm reflectivity for which the SNR equals one. The sensitivity of FDOCT is found to be higher than TDOCT, especially in low light conditions. The paper also discusses the effects of DFT on signal amplitude and noise, and the importance of minimizing exposure time and subtracting reference arm signals to reduce coherent noise. The results show that FDOCT has a significant advantage in sensitivity and is suitable for low light situations such as high-speed imaging. The paper concludes that FDOCT is the preferred method for such applications.