Glossary¶
- precomputed¶
A chunked storage format for volumetric data that relies on
infofiles
to keep track of the volume’s metadata, used by neuroglancer. See the documentation.- CloudVolume, cv¶
A serverless Python client for reading and writing in precomputed format. Supports local, AWS S3, and GCS. Relies on service tokens. See the documentation.
- Neuroglancer, ng¶
WebGL-based viewer for volumetric data in precomputed format. See the documentation.
- GCP¶
Google Cloud Platform. Supported by
zetta_utils.mazepa
for executing tasks remotely using Kubernetes.- SQS¶
Amazon’s Simple Queue Service. Supported by
zetta_utils.mazepa
for keeping track of task executions when executing tasks remotely.- MIP, MIP level¶
Multum in parvo. Refers to the resolution of volumetric data, with MIP 0 being the highest resolution and successive MIPs being downsampled by a factor of 2 in XY. Used to reduce the data size.
- EM¶
Electron microscopy.
- SEM¶
Scanning Electron Microscopy.
- FIB-SEM¶
Focused Ion Beam Scanning Electron Microscopy.
- TEM¶
Transmission Electron Microscopy.
- Section¶
An individual slice of tissue. A section is reprented by some Z value.
- Alignment¶
The process of warping volumetric data so that the images seem to move smoothly in Z. Each section is warped by a field to produce an alignment.
- Field¶
A layer specifying 2 dimensional vector for each point in 3 dimensional space. Used to represent how the pixels should move for warping images.
zetta_utils
usestorchfields
to handle fields.- Inference¶
In
zetta_utils
pipeline context, usually refers to inferring the affinities for a dataset.- Affinities¶
The probabilities in 3 dimensions for each voxel of a dataset, representing the likelihood that the voxel belongs to the same cell as its neighbour.
- Watershed¶
In
zetta_utils
pipeline context, using watershed on the affinities to break the volume down into a bunch of small volumes.- Agglomeration¶
The process of merging the small volumes generated by watershed into full cells.
- Segmentation¶
The process of dividing an image volume into many small 3D objects, or the collection of the 3D objects. Requires running inference to get affinities, watersheding, and agglomeration.
- ACED¶
State-of-the-art alignment pipeline developed by Zetta AI.
- Mazepa¶
An event-driven task queue library used by
zetta_utils
. See zetta_utils.mazepa for details.- Task¶
The individual units of work that need to be executed. See zetta_utils.mazepa for details.
- Operation¶
A wrapper for constructing Tasks. See zetta_utils.mazepa for details.
- Flow¶
A definition of the workflow specifying the order of and dependencies between tasks. See zetta_utils.mazepa for details.
- FlowSchema¶
A wrapper for constructing Flows. See zetta_utils.mazepa for details.