ICIP 2022 Challenge on Parasitic Egg Detection and Classification in Microscopic Images: Dataset, Methods and Results
This work addresses the need for automated systems to detect intestinal parasitic infections, but it is incremental as it focuses on summarizing existing methods and results from a challenge.
The paper reviews the ICIP 2022 Challenge, which tackled the problem of automating parasitic egg detection and classification in microscopic images to address time-consuming manual analysis, and it introduces the largest dataset of its kind for this application.
Manual examination of faecal smear samples to identify the existence of parasitic eggs is very time-consuming and can only be done by specialists. Therefore, an automated system is required to tackle this problem since it can relate to serious intestinal parasitic infections. This paper reviews the ICIP 2022 Challenge on parasitic egg detection and classification in microscopic images. We describe a new dataset for this application, which is the largest dataset of its kind. The methods used by participants in the challenge are summarised and discussed along with their results.