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README.md

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-license: mit
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+---
+license: mit
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+
+### 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](http://oocystmeter.org/)  
+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 <i>Plasmodium falciparum</i> 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
+<i>Anopheles gambiae</i> mosquito midgut infected with <i>Plasmodium falciparum</i> oocysts
+