license: mit
Dataset Description
We created a training dataset comprising 11,178 oocysts collected from 231 images from midguts dissected at day 7–9 post infection.
Using this dataset we trained a machine learning model to count and size oocysts in mercurochrome-stained mosquito midguts.
See the oocyst counting/sizing tool here
Preprint coming soon
Dataset summary
This dataset includes 231 panoramic images of mosquito midguts imaged at 100x or 200x magnification.
The midguts were stained with mercurochrome to reveal Plasmodium falciparum oocysts.
Oocysts were manually labeled with the VGG Image Annotator (VIA) using ellipses tracing their outline as drawn by trained parasitologists.
We also labeled the outline of each midgut using the “polygon region shape” function.
The annotations were saved in json format and split into the same train and test split used to train the OocystMeter model.
Species
Anopheles gambiae mosquito midgut infected with Plasmodium falciparum oocysts