HuBMAP Autofluorescence Microscopy (AF)

Last Updated: 6/15/2020


This document details AF data states, metadata fields, file structure, QA/QC thresholds, and data processing.


Autofluorescence microscopy exploits endogenous fluorescence in a biological tissue to capture an image. The image can then be used to integrate other images from multiple modalities and to align tissues within a 3D experiment. Autofluorescence microscopy requires no sample preparation and can be performed on any fluorescence microscope.


There are a variety of terms used in this document that may not be familiar to all researchers wanting to make use of the HubMap data. The following figures illustrate several of these terms:

Figure 1: Pictorial representation of microscopy terms. The black box is an example slide or cover slip where the sample is located. Blue boxes are examples of “regions” or user defined imaging areas. For instance, if you want to image a specific structure in the tissue, you would designate a “region” over the structure. Red boxes are examples of “tiles” or the microscope “field of view”. The size of the tile is dependent on the microscope set up and objective. Tiles will fill the region. Because the field of view cannot be changed, tiles will overhang from the region, ensuring the entire region is imaged at the expense of extra tiles being acquired.

Figure 2: Images are generally acquired with adjacent tiles overlapping, as indicated by the dark regions in the image on the right above. Overlap enhances alignment of tiles for stitching to create a composite image, as shown in Figure 4 below.

Figure 3: Images of tiles are captured as the stage moves across the imaged region row by row (left) or via a serpentine (or snake-like) path (right).

Figure 4: Stitching is the process of aligning and merging neighboring image tiles into a single composite image.

HuBMAP AF Data States (Levels):

Data State Description Example File Type
0 Raw image data: This is the data that comes directly off the microscope without preprocessing; sometimes referred to as tiled or unstitched data. (may not always be included). CZI, TIFF
1 Processed Microscopy data: Can include stitching, thresholding, background subtraction, z-stack alignment, deconvolution CZI, TIFF, OME-TIFF
2 Segmentation: Computationally predicted cell (nucleus, cytoplasm) and/or structural boundaries (tubules, ventricles, etc.) CSV, TIFF
3 Annotation (Cells and Structures): Interpretation of microscopy image and/or segmentation in terms of biology (e.g. unhealthy vs healthy, cell-type, function, functional region). TIFF, PNG

HuBMAP Metadata:

This metadata schema is now available in Github for download.

Associated Metadata files:

Metadata File Name File Type Field Definition
OME-TIFF OME-TIFF SchemaType Metadata schema type
    SchemaVersionMajor Metadata schema version - major
    SchemaVersionMinor Metadata schema version - minor
    Name Name of the microscopy image
    AcquisitionDate Date and Time of Acquisition
    PhysicalSizeX Spatial Resolution in x dimension (Pixel Size)
    PhysicalSizeY Spatial Resolution in y dimension (Pixel Size)
    SizeX Number of Pixels
    SizeY Number of Pixels
    SizeZ Number of Pixels
    Channel:0:0 DAPI Channel
    Channel:0:1 FITC Channel
    Channel:0:2 TRITC Channel
Instrument Metadata XML SchemaType Metadata schema type
    Device Microscope used
    TheoreticalTotalMagnification Objective Magnification
    DAPI ExposureTime Exposure time for DAPI Channel
    DAPI DyeMaxEmission DAPI Max Emission
    DAPI DyeMAxExcitation DAPI Max Excitation
    EGFP ExposureTime Exposure time for EGFP Channel
    EGFP DyeMaxEmission EGFP Max Emission
    EGFP DyeMAxExcitation EGFP Max Excitation
    DsRed ExposureTime Exposure time for DsRed Channel
    DsRed DyeMaxEmission DsRed Max Emission
    DsRed DyeMaExcitation DsRed Max Excitation
    Detector ID Type of Detector/Camera used
    Intensity Fluorescence Lamp Intensity
    SchemaType Metadata schema type
    Device Microscope used
    TheoreticalTotalMagnification Objective Magnification
CCF Spatial Metadata JSON alignment_id Unique identifier given to each instance of the Registration UI running in a user’s web browser
    alignment_operator_first_name Person who aligned tissue to CCF-First Name
    alignment_operator_last_name Person who aligned tissue to CCF - Last Name
    alignment_datetime Date and time tissue was aligned to CCF
    reference_organ_id Identifier for the reference organ the sample is registered to
    tissue_position_mass_point_x x position of the center of mass of the tissue sample in relation to the 3-D grid wrapped around the reference organ
    tissue_position_mass_point_y y position of the center of mass of the tissue sample in relation to the 3-D grid wrapped around the reference organ
    tissue_position_mass_point_z z position of the center of mass of the tissue sample in relation to the 3-D grid wrapped around the reference organ
    tissue_object_rotation_x Rotation of the tissue sample around the x-axis of its mass point
    tissue_object_rotation_y Rotation of the tissue sample around the y-axis of its mass point
    tissue_object_rotation_z Rotation of the tissue sample around the z-axis of its mass point
    tissue_object_size_x Size of the x-dimension of the tissue sample
    tissue_object_size_y Size of the y-dimension of the tissue sample
    tissue_object_size_z Size of the z-dimension of the tissue sample
    section_number Tissue Section number. Each section is 10µm thick.

Terms defined in this document:

Term Definition
Intensity Detector Counts
Signal Intensity produced by fluorescence, both endogenous and introduced
Noise Intensity not produced by light but electronic fluctuations or electronic background.
Stitching Image stitching is the process of combining multiple images (tiles) with overlapping fields of view to produce a single, large image.
Alignment/Registration Image registration is the process of transforming different images into one coordinate system. Registration of all channels in each cycle is performed.
Deconvolution Deconvolution refers to reversing the optical distortion that takes place in an optical microscope to sharpen images/ improve definition. Practically, deconvolution can also sharpen images that suffer from fast motion or jiggles during capturing.
Channels Name of the fluorescence excitation wavelengths used. May be expressed as a fluorophore name (e.g. DAPI, GFP, DsRED, Cy5), wavelength (e.g. 488, 540, 750), or color (e.g. green, red, blue).
Regions User defined imaging area.
Autofluorescence/Background Endogenous fluorescence signal.
Z-stack A series of images produced at different stage heights or z positions.
X plane Plane that determines width
Y plane Plane that determines height
Z plane Plane that determines depth
Pitch Distance between pixels
Tile Rectangular field-of-view (Figure 1).
Pixel How close two objects can be and still be differentiated within an image. This is generally dependent upon the diffraction limit of light and the microscope objective.
Field of View Angle through which light can reach the detector. Available imaging area without stage movement.

For Additional Help:

Please contact: Jeffrey Spraggins