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greenelab / deep-review

A collaboratively written review paper on deep learning, genomics, and precision medicine
https://greenelab.github.io/deep-review/
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Automating Morphological Profiling with Generic Deep Convolutional Networks #129

Open agitter opened 7 years ago

agitter commented 7 years ago

http://doi.org/10.1101/085118 (http://biorxiv.org/content/early/2016/11/02/085118)

Morphological profiling aims to create signatures of genes, chemicals and diseases from microscopy images. Current approaches use classical computer vision-based segmentation and feature extraction. Deep learning models achieve state-of-the-art performance in many computer vision tasks such as classification and segmentation. We propose to transfer activation features of generic deep convolutional networks to extract features for morphological profiling. Our approach surpasses currently used methods in terms of accuracy and processing speed. Furthermore, it enables fully automated processing of microscopy images without need for single cell identification.

cgreene commented 7 years ago

Tagging @AnneCarpenter since we talked about this a bit, I think, when she visited Penn. I think this would be related to study.