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navigate.model.features.common_features.FindTissueSimple2D

class navigate.model.features.common_features.FindTissueSimple2D(model, overlap=0.1, target_resolution='Nanoscale', target_zoom='N/A')

Bases: object

FindTissueSimple2D class for detecting tissue and gridding out the imaging space in 2D.

This class is responsible for detecting tissue, thresholding, and gridding out the space for 2D imaging. It processes acquired frames to determine regions of interest (tissue), calculates offsets, and generates grid positions for imaging.

__init__(model, overlap=0.1, target_resolution='Nanoscale', target_zoom='N/A')

Initialize the FindTissueSimple2D class.

Parameters:

modelMicroscopeModel

The microscope model object used for tissue detection and gridding.

overlapfloat, optional

The overlap percentage between grid tiles. Default is 0.1 (10%).

target_resolutionstr, optional

The target resolution for imaging (e.g., “Nanoscale”). Default is “Nanoscale”.

target_zoomstr, optional

The target zoom level for imaging. Default is “N/A”.

Methods

__init__(model[, overlap, ...])

Initialize the FindTissueSimple2D class.

data_func(frame_ids)

Process acquired frames for tissue detection, thresholding, and grid calculation.

Attributes

model

The microscope model associated with tissue detection and

config_table

A dictionary defining the configuration for tissue detection and

overlap

The overlap percentage between grid tiles.

target_resolution

The target resolution for imaging (e.g., "Nanoscale").

target_zoom

The target zoom level for imaging.

data_func(frame_ids)

Process acquired frames for tissue detection, thresholding, and grid calculation.

This method processes acquired frames to detect tissue regions, apply thresholding, and calculate grid positions for imaging. It performs the following steps: - Downsamples the acquired image based on desired magnification change. - Applies thresholding using Otsu’s method. - Calculates the bounding box of the tissue region. - Computes offsets for gridding based on acquired and target resolutions. - Grids out the 2D imaging space based on the specified overlap percentage.

Parameters:

frame_idslist

A list of frame IDs corresponding to acquired frames.

config_table

A dictionary defining the configuration for tissue detection and

Type:

dict

model

The microscope model associated with tissue detection and

Type:

MicroscopeModel

overlap

The overlap percentage between grid tiles.

Type:

float

target_resolution

The target resolution for imaging (e.g., “Nanoscale”).

Type:

str

target_zoom

The target zoom level for imaging.

Type:

str

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