ml - Finding the optimal threshold

None

Paramètres

ListOf_Input_Image: ListOf( Volume 3D ) ( input )

ListOf_Input_Segmented_Image: ListOf( Graph ) ( input )

Class_Of_Interest: String ( input )

Output_Model: Any Type ( optional, sortie )

ListOf_Output_Segmented_Image: ListOf( Volume 3D ) ( optional, output )

Informations techniques

Toolbox : Bioprocessing

Niveau d'utilisateur : 0

Identifiant : ml_optimal_threshold

Nom de fichier : brainvisa/toolboxes/bioprocessing/processes/research/toolbox/machine_learning/ml_optimal_threshold.py

Supported file formats :

ListOf_Input_Image :

gz compressed NIFTI-1 image, Aperio svs, DICOM image, Directory, ECAT i image, ECAT v image, FDF image, FreesurferMGH, FreesurferMGZ, GIS image, Hamamatsu ndpi, Hamamatsu vms, Hamamatsu vmu, JPEG image, Leica scn, MINC image, NIFTI-1 image, SPM image, Sakura svslide, TIFF image, TIFF image, TIFF(.tif) image, TIFF(.tif) image, Ventana bif, Zeiss czi, gz compressed MINC image, gz compressed NIFTI-1 image

ListOf_Input_Segmented_Image :

Graph and data, Graph and data

Output_Model :

pickle file, pickle file

ListOf_Output_Segmented_Image :

gz compressed NIFTI-1 image, Aperio svs, DICOM image, Directory, ECAT i image, ECAT v image, FDF image, FreesurferMGH, FreesurferMGZ, GIS image, Hamamatsu ndpi, Hamamatsu vms, Hamamatsu vmu, JPEG image, Leica scn, MINC image, NIFTI-1 image, SPM image, Sakura svslide, TIFF image, TIFF image, TIFF(.tif) image, TIFF(.tif) image, Ventana bif, Zeiss czi, gz compressed MINC image, gz compressed NIFTI-1 image