Toward Generalizable Whole Brain Representations with High-Resolution Light-Sheet Data

Minyoung E. Kim, Dae Hee Yun, Aditi V Patel, Madeline Hon, Taegeon Lee, Webster Guan, Brian Nguyen

Submission Track: Short papers presenting ongoing research or work submitted to other venues (up to 5 pages, excluding references)

Keywords: benchmark, benchmark data, biomedical data, light-sheet microscopy data, brain data, machine learning, neuroscience, the brain

TL;DR: We present CANVAS, a large-scale light-sheet benchmark dataset of intact whole mouse brains at subcellular resolution, along with extensive cell annotations. It aims to address the challenges of analyzing petabyte-scale 3D microscopy data.

Abstract:

Unprecedented visual details of biological structures are being revealed by
subcellular-resolution whole-brain 3D microscopy data, enabled by recent advances
in intact tissue processing and light-sheet fluorescence microscopy (LSFM).
These volumetric data offer rich morphological and spatial cellular information,
however, the lack of scalable data processing and analysis methods tailored to
these petabyte-scale data poses a substantial challenge for accurate interpretation.
Further, existing models for visual tasks such as object detection and classification
struggle to generalize to this type of data. To accelerate the development of suitable
methods and foundational models, we present CANVAS, a comprehensive set
of high-resolution whole mouse brain LSFM benchmark data, encompassing six
neuronal and immune cell-type markers, along with a set of cell annotations and a
leaderboard. We also demonstrate challenges in generalization of baseline models
built on existing architectures, especially due to the heterogeneity in cellular morphology
across phenotypes and anatomical locations in the brain. To the best of
our knowledge, CANVAS is the first and largest LSFM benchmark capturing intact
mouse brain tissue at subcellular level, and includes extensive annotations of cells
throughout the brain.

Submission Number: 20