The invention discloses a
visual monitoring method assisted by an AI image
recognition algorithm in a transparent working sleeve under a spine
endoscope, and relates to the technical field of
medical instruments, and the method comprises the following steps: collecting a torque waveform, a
perfusion pressure
signal and a
cavity pressure signal under a unified event time
base line, constructing a
resonance frequency band spectrum, and obtaining a
resonance frequency band spectrum; calculating a
resonance pressure index and extracting a phase evolution trajectory for liquid level
distortion reconstruction; and under the constraint of the resonance
pressure index and the phase evolution trajectory, recovering the liquid level phase, reconstructing a lens phase field in front of the camera, calculating a view
distortion gradient, and determining a liquid level dynamic
distortion core area. According to the method, a resonance dynamic map is constructed through multi-
source data fusion, a liquid level
potential field is reconstructed, a visual field distortion area is locked, artifacts are eliminated in combination with image
feature recognition,
perfusion control is reversely driven based on a reliable visual field state, and a closed-loop regulation and control strategy with time reversal gating and self-adaptive updating capacity is formed. And stable and
intelligent control of the visual field in the operation is realized.