Electron microscopy (EM) is a technique that exploits the interaction between electron and matter to produce high resolution images down to atomic level. In order to avoid undesired scattering in the electron path, EM samples are conventionally imaged in solid state under vacuum conditions. Recently, this limit has been overcome by the realization of liquid-phase electron microscopy (LP EM), a technique that enables the analysis of samples in their liquid native state. LP EM paired with a high frame rate acquisition direct detection camera allows tracking the motion of particles in liquids, as well as their temporal dynamic processes. In this research work, LP EM is adopted to image the dynamics of particles undergoing Brownian motion, exploiting their natural rotation to access all the particle views, in order to reconstruct their 3D structure via tomographic techniques. However, specific computer vision-based tools were designed around the limitations of LP EM in order to elaborate the results of the imaging process. Consequently, different deblurring and denoising approaches were adopted to improve the quality of the images. Therefore, the processed LP EM images were adopted to reconstruct the 3D model of the imaged samples. This task was performed by developing two different methods: Brownian tomography (BT) and Brownian particle analysis (BPA). The former tracks in time a single particle, capturing its dynamics evolution over time. The latter is an extension in time of the single particle analysis (SPA) technique. Conventionally it is paired to cryo-EM to reconstruct 3D density maps starting from thousands of EM images by capturing hundreds of particles of the same species frozen on a grid. On the contrary, BPA has the ability to process image sequences that may not contain thousands of particles, but instead monitors individual particle views across consecutive frames, rather than across a single frame
