Multiaxial neutron/x-ray imaging and three-dimensional (3D) reconstruction techniques play a crucial role in gaining valuable insights into the generation and evolution mechanisms of pulsed radiation sources. Owing to the short emission time (∼200 ns) and drastic changes of the pulsed radiation source, it is necessary to acquire projection data within a few nanoseconds in order to achieve clear computed tomography 3D imaging. As a consequence, projection data that can be used for computed tomography image reconstruction at a certain moment are often available for only a few angles. Traditional algorithms employed in the process of reconstructing 3D images with extremely incomplete data may introduce significant distortions and artifacts into the final image. In this paper, we propose an iterative image reconstruction method using cylindrical harmonic decomposition and a self-supervised denoising network algorithm based on the deep image prior method. We augment the prior information with a 2D total variation prior and a 3D deep image prior. Single-wire Z-pinch imaging experiments have been carried out at Qin-1 facility in five views and four frames, with a time resolution of 3 ns for each frame and a time interval of 40 ns between adjacent frames. Both numerical simulations and experiments verify that our proposed algorithm can achieve high-quality reconstruction results and obtain the 3D intensity distribution and evolution of extreme ultraviolet and soft x-ray emission from plasma.