In the yellow fever studies, methods to quantify neutralizing antibodies are crucial and contribute to the development and evaluation of new antiviral vaccines effectiveness. The assay most commonly used for this purpose is the Plaque-Reduction Neutralization Test (PRNT), but this assay is time-consuming, not amenable to a large number of samples, and difficult to adapt to a high throughput routine. PRNT variations like FRNT and microFRNT were designed to mitigate these bottlenecks, but also tend to have large variations among different analysts due to visual plaque recognition and manual counting errors. Therefore, providing faster and more accurate methods for image acquiring and plaque/focus counting to the neutralizing antibodies assays could minimize human inherent variations. Innovations such as automation at critical steps can increase throughput, reduce rework, and generate more accurate results. Companies specialized in microscopy, robotics, and information technology developed robust systems able to standardize the image acquisition and analysis for neutralization assays, which could aid the public health response to emerging viral diseases. In this context, these automated systems aim to obtain images and to identify morphological patterns, setting the best ranges for some parameters from structures of interest, such as circularity, size, color intensity, etc. In this session, we describe the use of automated image acquisition and quantification procedures to increase serum neutralization assays throughput and improving their results accuracy.