Automatic segmentation method for CFU counting in single plate-serial dilution

Quantification of colony forming units (CFU) on microbial cultures prepared according to the standard spread plate technique is a daily laboratory routine that requires significant resources. On the other hand, SP-SDS (Single Plate Serial Dilution Spotting) is a widely used technique that allows a great reduction in the use of material resources and time. However, previous approaches for automatic quantification are based on images of standard spread plate Petri dishes with low variation of CFU features and captured under controlled lighting conditions. In this paper, we propose a novel approach that automatically separates each dilution in images of Petri dishes prepared in the SP-SDS technique and counts total CFU per dilution, which most approaches are unable to perform. The proposed approach employs region-based shape descriptors for quantification of isolated CFU and cross-correlation granulometry for the quantification of CFU in agglomerates. For the experiments, we composed two image datasets and used images from two publicly available datasets. The images from our datasets were acquired under real laboratory ambient conditions and show variation in lighting, background noise, low contrast between bacterial colonies and background, and high variation in CFU features. Overall, the results obtained by our approach in terms of accuracy, precision, and sensitivity were superior to those of two other approaches recently proposed in the literature used for comparison in this study, especially for high-definition images. In addition, our results present greater or similar accuracy to various approaches found in the literature, most of which are not able to count CFU in images obtained from Petri dishes prepared in the SP-SDS technique and low control of ambient conditions. Our composed datasets are publicly available for download as a contribution to further research.