A. Murat Maga

Professor, Department of Pediatrics (Craniofacial Medicine), University of Washington

Principal Investigator, Center for Developmental Biology & Regenerative Medicine, Seattle Children's Research Institute

Director, MicroCT & Image Analysis Lab, Seattle Children's Research Institute

A quantitative morphologist studying the genetics and morphometrics of craniofacial development in mammals using 3D imaging — and building the open-source tools that make that science reproducible and shareable.

✉ Email ORCID GitHub Seattle Children's profile

About

University of Washington · Seattle Children's Research Institute

I am a professor in the University of Washington Department of Pediatrics, Division of Craniofacial Medicine, and a principal investigator at the Center for Developmental Biology and Regenerative Medicine at Seattle Children's Research Institute. My lab investigates the genetic and environmental factors that shape the development of the skull, combining high-resolution 3D imaging (microCT) with quantitative shape analysis and machine learning.

Alongside this research, my group develops and maintains SlicerMorph, an open-source 3D morphometrics toolkit for the 3D Slicer platform, together with a broader ecosystem — MorphoCloud and MorphoDepot — that lowers the barrier to high-performance computing and collaborative anatomical data analysis for the biology, anthropology, and morphology communities.

Research

Genetics & morphometrics of craniofacial development · open, reproducible 3D morphology

My research sits at the intersection of developmental biology, evolutionary morphology, and computational image analysis. Using mouse models and large imaging collections, I study how genes and environment drive variation in craniofacial form, and develop the geometric morphometric and deep-learning methods needed to quantify that variation at scale.

A second, tightly linked thread is research infrastructure: making advanced 3D image analysis accessible, reproducible, and collaborative through open-source software, cloud computing, and shared data workflows.

3D morphometrics Geometric morphometrics Craniofacial development microCT imaging Computational anatomy Shape analysis Deep learning for morphology Automated landmarking Bone morphometry Evolutionary biology

Genetic & environmental control of skull shape
Automated landmarking & segmentation of 3D anatomy
Deep learning for high-throughput phenotyping
Mouse models of structural birth defects
Open infrastructure for digital morphology

MicroCT & Image Analysis Lab

Director · Seattle Children's Research Institute, Jack MacDonald Building

I direct the microCT and image analysis lab at Seattle Children's Research Institute — a shared instrumentation resource for non-destructive, high-resolution 3D imaging of biological and paleontological specimens, from mouse embryos and soft tissues to fossils and insects.

The facility is built around a Bruker/Skyscan 1272 scanner and pairs it with an open analysis workflow in 3D Slicer and SlicerMorph, plus sample datasets, specimen-preparation protocols, and tutorials for new users. It was established with support from an NIH/OD S10 shared instrumentation grant.

Visit the facility page →

Instrument

ScannerBruker/Skyscan 1272 (CMOS)
Camera modes512 · 1K · 2K · 4K
Resolution52.3 – 6.125 µm
Specimenstissue, embryos, fossils, insects
Analysis3D Slicer + SlicerMorph

Registered as the Seattle Children's Research Institute Micro Computed Tomography Imaging and Visualization Lab Core Facility — please cite as RRID:SCR_024678.

Open-source projects

A connected ecosystem for 3D digital morphology, built and maintained by my lab

slicermorph.org

SlicerMorph

An open and extensible platform to retrieve, visualize, measure, and analyze 3D morphology — geometric morphometrics, automated landmarking (ALPACA), and more, inside 3D Slicer.

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morphocloud.org

MorphoCloud

A cloud-powered, open-source platform that democratizes access to high-performance computing for morphological data analysis — run SlicerMorph in your browser on powerful virtual machines.

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morphodepot.org

MorphoDepot

A git- and GitHub-based workflow for collaborative 3D anatomical segmentation — bringing the open-source fork-and-contribute model to digital morphology and the classroom.

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Selected publications

Full list on ORCID · Google Scholar

2026Anatomy-aware, label-informed approach improves image registration for challenging datasets
PLOS ONE
2026Forking anatomy: how MorphoDepot applies the open-source development model to 3D digital morphologyMorphoDepot
Methods in Ecology and Evolution
2026MorphoCloud: democratizing access to high-performance computing for morphological data analysisMorphoCloud
F1000Research
2025SlicerMorph Photogrammetry: an open-source photogrammetry workflow for reconstructing 3D models
Biology Open
2025Streamlining asymmetry quantification in fetal mouse imaging: a semi-automated pipeline supported by expert guidance
Developmental Dynamics
2025Leveraging descriptor learning and functional map–based shape matching for automated anatomical landmarking in mouse mandibles
Journal of Anatomy
2025Easier said than done: unexpected hurdles to preparing ~1,000 cranial CT scans for data collection from an online digital repository
PeerJ
2023DeCA: a Dense Correspondence Analysis toolkit for shape analysis
Shape in Medical Imaging (ShapeMI), Springer LNCS 14350
2023Deep learning–enabled multi-organ segmentation of mouse embryosMEMOS
Biology Open
2022Automated landmarking via multiple templatesMALPACA
PLOS ONE
2021ALPACA: a fast and accurate computer vision approach for automated landmarking of three-dimensional biological structuresALPACA
Methods in Ecology and Evolution
2021SlicerMorph: an open and extensible platform to retrieve, visualize and analyse 3D morphologySlicerMorph
Methods in Ecology and Evolution
2021Comparing semi-landmarking approaches for analyzing three-dimensional cranial morphology
American Journal of Physical Anthropology
2018Mapping genetic variants for cranial vault shape in humans
PLOS ONE

Research funding

Selected federal grants (NSF & NIH) supporting the lab's research and infrastructure

MorphoCloud: a cloud-powered, open-source platform for research, teaching and collaboration in 3D digital morphology

NSF 2301405 · 2024–2028 · active
HDR Institute: Imageomics — a new frontier of biological information powered by knowledge-guided machine learning

NSF 2118240 · 2021–2026 · active
Utilization of advanced technologies for the understanding of human structural birth defects (P01)

NIH / NICHD P01HD104435 · 2021–2025
High-resolution ex vivo microCT for biomedical imaging (instrumentation)

NIH Office of the Director S10OD032302 · 2022–2023
Deep phenotyping of 3D data for candidate gene selection from Kids First studies

NIH Office of the Director R03OD032627 · 2021–2022
An integrated platform for retrieval, visualization and analysis of 3D morphology from digital biological collections

NSF 1759883 · 2018–2021
Biology-guided neural networks for discovering phenotypic traits

NSF 1939505 · 2019–2021
Inbred mouse strains: an untapped resource for genome-wide association of craniofacial shape

NIH / NIDCR R03DE027110 · 2017–2019

Teaching & outreach

Training the digital morphology community through short courses and an open user group

Short courses

SlicerMorph 101 — Introduction to 3D digital morphology with SlicerMorph.
SlicerMorph 102 — 3D morphometrics with SlicerMorph.
Taught online and in person at the UW Friday Harbor Labs, plus bootcamps and conference workshops (SICB, Evolution, Anatomy Connected).

Community & upcoming

Monthly — SlicerMorph user check-in, 1st Wednesday at 9:00 PT (online).
Mar 3–6, 2026 — SlicerMorph in the Classroom BootCamp, Seattle, WA.
Join the SlicerMorph announcements list for meeting links and new course dates.