Growth of marine bivalve aquaculture is presented as a potential measure to effectively provide seafood for human consumption while preserving wild populations. It can be an economic driver in coastal areas while also providing important ecosystem services such as filtration of phytoplankton and carbonate buffering. However, as with any other farming practices, increased densities of individuals in a confined space often result in disease outbreaks. Pathogens developing in these conditions can easily spread among farmed stocks, affecting all the production lines and potentially causing adverse economic consequences, spreading over large areas and eventually affecting wild populations as well. Development and implementation of early detection methods for pathogen infection are imperative to maintain and expand aquaculture activities. In this context, a new method to quantify and characterize infection by Vibrio aestuarianus in the Pacific oyster, Magallana gigas, based on image analysis of histological slides stained by immunohistochemistry is presented. The method is used to automatically measure the proportion of tissue infected by IHC-stain bacteria from each image and to characterize bacteria spread in the tissue. The proportion of tissue infected by IHC-stained bacteria and spatial dispersion indexes, used to characterize 2D bacterial dispersion, were directly associated with the quantity of bacteria previously measured by qPCR. All of these results suggest a pattern of infection where V. aestuarianus tends to be more clustered and less randomly spread in the organism with increased infection. Advantages, limitations, and potential ways to improve the method are discussed.