Compressed sensing (CS) has a wide range of applications in sparse signal reconstruction. Aiming at the problems of low recovery accuracy and long reconstruction time of existing reconstruction algorithms in medical imaging, this paper proposes a corrected smoothing L0 algorithm based on compressed sensing (CSL0). Firstly, an approximate hyperbolic tangent function (AHTF) which is more similar to the L0 norm is proposed to approximate the L0 norm. Secondly, aiming at the problem that the steepest descent method has a “sawtooth phenomenon” and the modified Newton method is sensitive to the initial value selection, the steepest descent method and the modified Newton method are jointly optimized to improve the reconstruction accuracy. In addition, the CCSL0 algorithm is proposed by introducing a composite inverse proportional function, and the reconstruction time of the CSL0 algorithm is further optimized. Finally, the CSL0 algorithm and CCSL0 algorithm are simulated on medical images. The results show that the proposed algorithm improves the reconstruction accuracy of the test image by 0 – 0.96 dB.