xmipp3.protocols.protocol_pick_noise module
- class xmipp3.protocols.protocol_pick_noise.XmippProtPickNoise(**args)[source]
Bases:
ProtParticlePicking,XmippProtocolProtocol designed pick noise particles in micrographs and not real particles. The protocol allows you to choose the number of noise particles to extract from each micrograph. Set to -1 for extracting the same amount of noise particles as the number true particles for that micrograph.
AI Generated
## Overview
The Pick Noise protocol generates coordinates corresponding to background or noise regions in micrographs, rather than to true particles.
The protocol starts from an existing set of particle coordinates. These input coordinates define where the real particles are expected to be. The protocol then selects additional coordinates in the same micrographs, but sufficiently far from the true particle positions, so that the selected boxes should mostly contain background noise.
The output is a new set of coordinates representing noise particles. These coordinates can be used to extract noise images for training, validation, particle screening, method development, or comparison with real particle images.
## Inputs and General Workflow
The main input is a set of true particle coordinates.
The protocol first writes the input coordinates into Xmipp .pos files, one per micrograph. These files are used by the noise-picking program to know which regions should be avoided.
The protocol then runs the Xmipp noise-picking tool on the directory containing the micrographs. For each micrograph, it selects coordinates away from the input particle coordinates. Finally, the generated noise coordinates are read back into Scipion as a new coordinate set.
The output coordinate set is linked to the same micrographs as the input coordinate set.
## Input Coordinates
The Input coordinates parameter should point to a SetOfCoordinates containing true particle positions.
These coordinates define the exclusion regions for noise picking. In other words, the protocol uses them to avoid selecting boxes that overlap with known particles.
The quality of the noise coordinates depends on the quality of the input particle coordinates. If the input set misses many particles, the protocol may accidentally select some real particles as noise. If the input set contains many false positives, valid background regions may be unnecessarily excluded.
For this reason, it is preferable to use a reasonably clean particle-coordinate set as input.
## Number of Noise Particles
The Number of noise particles parameter controls how many noise coordinates are selected from each micrograph.
If a positive number is provided, the protocol tries to select that number of noise coordinates per micrograph.
If the value is set to -1, the protocol selects the same number of noise coordinates as the number of true particle coordinates in each micrograph.
The -1 option is useful when the user wants a balanced set of particle and noise examples. For example, if a micrograph contains 120 particle picks, the protocol will try to generate 120 noise picks for that micrograph.
## Box Size
The protocol uses the box size stored in the input coordinate set.
This box size defines the approximate region that would be extracted around each coordinate. It is important because noise coordinates should be far enough from true particles that the extracted noise boxes do not contain particle signal.
If the box size is too small, the exclusion around particles may be too small. If it is too large, the protocol may reject too many possible background positions, especially in crowded micrographs.
The output noise coordinate set keeps the corresponding box-size information.
## Noise Coordinates
The coordinates produced by this protocol should be interpreted as background or non-particle positions.
They are not guaranteed to contain pure noise in a strict physical sense. Depending on the micrograph, some boxes may include ice features, carbon, contamination, detector artifacts, or very weak unpicked particles. However, they are selected to avoid the known particle coordinates.
This makes them useful as negative examples: image boxes that should not represent true particles according to the input coordinate set.
## Output Coordinates
The main output is outputCoordinates, a SetOfCoordinates containing the picked noise positions.
This output is associated with the same micrographs as the input coordinates. It can be passed to particle extraction protocols to extract noise boxes using the same extraction logic used for true particles.
The output is especially useful when paired with the original particle coordinates. The user can extract both real particles and noise particles and compare them in later workflows.
## Typical Uses
Noise coordinates can be useful in several situations.
They can be used to train or evaluate particle-picking classifiers, where real particles are positive examples and noise boxes are negative examples.
They can help test particle-screening methods by providing a known background class.
They can be useful for estimating background statistics or for comparing particle images with non-particle image patches.
They can also be used in method-development workflows where algorithms need examples of both signal and noise.
## Interpretation and Limitations
The protocol assumes that regions far from known particle coordinates are reasonable noise candidates.
This assumption is useful but not perfect. If the micrograph contains many unpicked particles, noise coordinates may include true particles. If the micrograph contains contamination or strong artifacts, some noise coordinates may correspond to structured non-particle features rather than simple background.
Therefore, the output should be interpreted as “background/noise candidates” rather than a perfectly pure noise set.
Visual inspection is recommended, especially if the noise coordinates will be used for training machine-learning models.
## Practical Recommendations
Use a clean and representative input coordinate set. The protocol can only avoid particles that are present in the input coordinates.
Use -1 for the number of noise particles when you want approximately the same number of noise examples as real particle examples per micrograph.
Use a fixed positive number when you want the same number of noise coordinates from every micrograph, regardless of particle density.
Inspect extracted noise boxes before using them for training or validation. Remove micrographs with strong contamination if they produce misleading negative examples.
Be careful with crowded micrographs. If particles are very dense, it may be difficult to find many background regions that are truly far from particles.
Remember that the protocol creates coordinates only. To obtain actual noise images, run an extraction protocol using the generated noise coordinates.
## Final Perspective
Pick Noise is a support protocol for generating negative examples from micrographs.
For biological users, its main value is that it creates a coordinate set of background regions that can be processed in parallel with true particle coordinates. This is useful for particle-picking validation, classifier training, background analysis, and quality-control workflows.
The protocol is most effective when the input particle coordinates are reliable and when the generated noise coordinates are visually checked before being used as negative examples.