Henrik Westerberg

The paper develops a convolutional neural network to automate MRI defacing quality control, reducing manual checks and improving efficiency.

MusMorph provides standardized mouse morphology data for meta-analyses, including craniofacial and brain structures across developmental stages and genotypes.

The paper introduces DeepCytometer, a deep learning pipeline for segmenting whole slides of mouse white adipose tissue, and uses it to analyze phenotypes in Klf14 mouse models.

LAMA automates 3D image analysis for mouse embryo phenotyping, integrating with an anatomical atlas to annotate dysmorphologies.

The paper integrates gene essentiality data from human and mouse screens to classify genes into FUSIL categories, identifying developmental lethal genes associated with rare diseases.