The Active Atlas: Combining 3D Anatomical Models with Texture Detectors
Yuncong Chen, Lauren McElvain, Alex Tolpygo, Daniel Ferrante, Harvey, Karten, Partha Mitra, David Kleinfeld, Yoav Freund

TL;DR
This paper introduces the Active Atlas, a novel digital brain atlas that integrates 3D anatomical models with texture analysis to automate and improve the localization of brain regions in histological studies.
Contribution
It presents a new methodology combining 3D organization and texture detection, creating detailed, automatically alignable brain atlases for regions lacking existing detailed maps.
Findings
Successfully created an atlas for mouse brainstem and mid-brain.
Enabled automatic alignment of histological data to the atlas.
Reduced manual labor in neuroanatomical localization.
Abstract
While modern imaging technologies such as fMRI have opened exciting new possibilities for studying the brain in vivo, histological sections remain the best way to study the anatomy of the brain at the level of single neurons. The histological atlas changed little since 1909 and localizing brain regions is a still a labor intensive process performed only by experienced neuro-anatomists. Existing digital atlases such as the Allen Brain atlas are limited to low resolution images which cannot identify the detailed structure of the neurons. We have developed a digital atlas methodology that combines information about the 3D organization of the brain and the detailed texture of neurons in different structures. Using the methodology we developed an atlas for the mouse brainstem and mid-brain, two regions for which there are currently no good atlases. Our atlas is "active" in that it can be…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMedical Image Segmentation Techniques · Cell Image Analysis Techniques · Advanced Image and Video Retrieval Techniques
