NEWS

---

simpleSeg 1.15.2 (2026-10-14)

• Tiled segmentation of large images supports pca, cellBody = "discModel" or cell body markers, and transform "tissueMask". The PCA and the cell body models are fitted on pixels sampled across the whole image (up to 100,000 and about 1,000,000), chosen by their position so that the sample does not depend on the tiles or the number of cores.
• Image files are opened once per process, which makes reading tiles much faster.
• Channel names are read from the band names of multi-band TIFF files.
• Pixels equal to a file's "no data" value (such as 255 in 8-bit TIFFs written by terra) keep that value instead of becoming missing.
• Cell body models no longer fail when the cell body signal is constant.

simpleSeg 1.15.1 (2026-10-14)

• cellBody = "discModel" and cell body markers work again for several images of the same size, and cell body markers work for a single image.
• An image where no nuclei pass the threshold gives a warning and an empty mask instead of an lm.fit error (#20).
• simpleSeg() checks that nucleus and tissue markers exist, and checks watershed, cellBody and cores; nucleus can be given as channel positions.
• normalizeCells() stops when imageID is missing and a per-image method is requested (#16, #22), and works with a single marker.
• Faster segmentation with lower memory use: each image is processed once in one task, on plain arrays, with fitted values from one QR fit.
• Parallel processing starts the BiocParallel workers once per call, runs BLAS with one thread per worker, and gives every image its own random number stream, so masks do not depend on the number of cores.
• simpleSeg() reads images from files: multi-channel files (OME-TIFF, QPTIFF, multi-page TIFF), folders of single-channel files (one image split by marker) and folders of such folders.
• New argument output: "masks", "cells" (a SpatialExperiment with the mean intensity of every channel, area and centroid of each cell, as from cytomapper::measureObjects()) or "none"; maskDir saves the masks as TIFF files. Paths return cells by default, images in R return masks.
• Images larger than tileSize are segmented tile by tile without reading them into memory; the cells and masks are those of the whole image.
• Gaussian smoothing is done in C++ (faster, and much less memory than the FFT used before; values agree to about 1e-13).
• Pixels of equal height are separated by a tiny amount (1e-6 of the tolerance) depending on their position before the watershed, so masks no longer depend on how ties are ordered. Masks from watershed = "distance", where most pixels are tied, and from transform "norm99" change slightly.
• PCA uses the markers that vary over the pixels it is fitted on.
• spatstat.geom and grDevices are no longer imported; terra is suggested (for reading files) rather than imported.

simpleSeg 0.99.7

• More changes based on the Bioconductor review process
• Modified test to make them more robust

simpleSeg 0.99.2

• Extensive reformatting for bioconductor
• Adding imports for functions
• Extended the description
• Added bug reports and url field
• added ggplot to suggestes
• Added news filedata generation script added
• Various improvements to the vignette
• Added unit tests
• Replaced sapply with vapply

simpleSeg 0.99.1 (2022-09-28)

• Bug fixing
• loading missing functions into NAMESPACE

simpleSeg 0.99.0 (2022-09-16)

• Initial bioconductor submission