syncell.imageprep

Functions

clean_labeled_mask(masks_nuc[, edge_buffer, ...])
expand_registered_images(imgs, tSet)	Apply transformations to a stack of images and expand images so they align :param imgs: images (Z,X,Y), registration along Z tSet: transformations for each image (angle, x-trans, y-trans) :type imgs: ndarray or list of images (each image same size) tSet: ndarray (NZ, 3) :return: expanded and registered image stack :rtype: ndarray (NZ, X, Y)
get_cell_intensities(img, labels[, averaging])
get_cyto_minus_nuc_labels(labels_cyto, ...)
get_images(filelist)	Get images from list of files.
get_labeled_mask(b_imgr[, imgM, ...])
get_mask_2channel_ilastik(file_ilastik[, ...])
get_masks(masklist[, fore_channel, ...])
get_registrations(imgs)	Apply pystackreg to get registrations along image stack :param imgs: images (Z,X,Y), registration along Z :type imgs: ndarray :return: set of transformations to register image stack, with the triplet (radial angle, x-translation, y-translation) for each image :rtype: ndarray (NZ,3), NZ number of images along Z
get_slide_image(imgs[, nrows, ncols, ...])	Construct slide image from a set of tiles (fields of view).
get_tile_order(nrows, ncols[, snake])	Construct ordering for to put together image tiles compatible with incell microscope.
get_voronoi_masks(labels[, imgM])
histogram_stretch(img[, lp, hp])	Histogram stretch of an array or image for normalization..
list_images(imagespecifier)	list images in a directory matching a pattern..
load_ilastik(file_ilastik)	Load ilastik prediction (pixel classification) from h5 file format.
local_threshold(imgr[, imgM, pcut, ...])
organize_filelist_fov(filelist[, fov_pos, ...])	Organize imagefiles in a list to field of view.
organize_filelist_time(filelist[, time_pos, ...])	Organize imagefiles in a list to timestamp ??d??h??m.
pad_image(img, maxedgex, maxedgey)
transform_image(x1, t)
znorm(img)	Variance normalization (z-norm) of an array or image)..