Multiplexed Fluorescence Imaging Research Articles

An Omni-Mesoscope for multiscale high-throughput quantitative phase imaging of cellular dynamics and high-content molecular characterization.

The mesoscope has emerged as a powerful imaging tool in biomedical research, yet its high cost and low resolution have limited its broader application. Here, we introduce the Omni-Mesoscope, a high-spatial-temporal and multimodal mesoscopic imaging platform built from cost-efficient off-the-shelf components. This system uniquely merges the capabilities of label-free quantitative phase microscopy to capture live-cell morphodynamics across thousands of cells with highly multiplexed fluorescence imaging for comprehensive molecular characterization. This Omni-Mesoscope offers a mesoscale field of view of ~5 square millimeters with a high spatial resolution down to 700 nanometers, enabling the capture of detailed subcellular features. We demonstrate its capability in delineating molecular characteristics underlying rare morphodynamic cellular phenomena, including cancer cell responses to chemotherapy and the emergence of polyploidy in drug-resistant cells. We also integrate expansion technique to enhance three-dimensional volumetric super-resolution imaging of thicker tissues, opening the avenues for biological exploration at unprecedented scales and resolutions.

Local Mean Suppression Filter for Effective Background Identification in Fluorescence Images.

We present an easy-to-use, nonlinear filter for effective background identification in fluorescence microscopy images with dense and low-contrast foreground. The pixel-wise filtering is based on comparison of the pixel intensity with the mean intensity of pixels in its local neighborhood. The pixel is given a background or foreground label depending on whether its intensity is less than or greater than the mean respectively. Multiple labels are generated for the same pixel by computing mean expression values by varying neighborhood size. These labels are accumulated to decide the final pixel label. We demonstrate that the performance of our filter favorably compares with state-of-the-art image processing, machine learning, and deep learning methods. We present three use cases that demonstrate its effectiveness, and also show how it can be used in multiplexed fluorescence imaging contexts and as a denoising step in image segmentation. A fast implementation of the filter is available in Python 3 on GitHub.

An Omni-Mesoscope for multiscale high-throughput quantitative phase imaging of cellular dynamics and high-content molecular characterization.

The mesoscope has emerged as a powerful imaging tool in biomedical research, yet its high cost and low resolution have limited its broader application. Here, we introduce the Omni-Mesoscope, a cost-effective high-spatial-temporal, multimodal, and multiplex mesoscopic imaging platform built from cost-efficient off-the-shelf components. This system uniquely merges the capabilities of quantitative phase microscopy to capture live-cell dynamics over a large cell population with highly multiplexed fluorescence imaging for comprehensive molecular characterization. This integration facilitates simultaneous tracking of live-cell morphodynamics across thousands of cells, alongside high-content molecular analysis at the single-cell level. Furthermore, the Omni-Mesoscope offers a mesoscale field of view of approximately 5 mm 2 with a high spatial resolution down to 700 nm, enabling the capture of information-rich images with detailed sub-cellular features. We demonstrate such capability in delineating molecular characteristics underlying rare dynamic cellular phenomena, such as cancer cell responses to chemotherapy and the emergence of polyploidy in drug-resistant cells. Moreover, the cost-effectiveness and the simplicity of our Omni-Mesoscope democratizes mesoscopic imaging, making it accessible across diverse biomedical research fields. To further demonstrate its versatility, we integrate expansion microscopy to enhance 3D volumetric super-resolution imaging of thicker tissues, opening new avenues for biological exploration at unprecedented scales and resolutions.

Multiplexed sequential imaging in living cells with orthogonal fluorogenic RNA aptamer/dye pairs.

Detecting multiple targets in living cells is important in cell biology. However, multiplexed fluorescence imaging beyond two-to-three targets remains a technical challenge. Herein, we introduce a multiplexed imaging strategy, 'sequential Fluorogenic RNA Imaging-Enabled Sensor' (seqFRIES), which enables live-cell target detection via sequential rounds of imaging-and-stripping. In seqFRIES, multiple orthogonal fluorogenic RNA aptamers are genetically encoded inside cells, and then the corresponding cell membrane permeable dye molecules are added, imaged, and rapidly removed in consecutive detection cycles. As a proof-of-concept, we have identified in this study four fluorogenic RNA aptamer/dye pairs that can be used for highly orthogonal and multiplexed imaging in living bacterial and mammalian cells. After further optimizing the cellular fluorescence activation and deactivation kinetics of these RNA/dye pairs, the whole four-color semi-quantitative seqFRIES process can be completed in ∼20 min. Meanwhile, seqFRIES-mediated simultaneous detection of critical signalling molecules and mRNA targets was also achieved within individual living cells. We expect our validation of this new seqFRIES concept here will facilitate the further development and potential broad usage of these orthogonal fluorogenic RNA/dye pairs for multiplexed and dynamic live-cell imaging and cell biology studies.

Systematic Structural Modification of Squaraine Dye for Near-Infrared Window One and Two Multiplexed In Vivo Imaging and Photothermal Therapy.

Due to the wide application of reporter gene-related visible/NIR-I bioluminescent imaging, multiplexed fluorescence imaging across visible/NIR-I/NIR-II has excellent potential in biomedical research. However, in vivo multiplexed imaging applications across those regions have rarely been reported due to the lack of proper fluorophores. Herein, nine squaraine dyes, which exhibit diverse adsorption and emission wavelengths, were synthesized. Among them, water-soluble SQ 710-5k and SQ 905 were found to have significant absorption differences, which allowed the tumor and lymph nodes to be identified. Then, for the first time, six-channel multiplexed fluorescence imaging across visible/NIR-I/II was achieved by coordination with reporter gene-related bioluminescent phosphors. Additional research revealed that SQ 710-5k exhibited higher-quality blood vessels and tumor imaging in NIR-II. H-aggregates SQ 905 demonstrated a high photothermal conversion efficiency for photothermal therapy. This study proposed an approach to creating small molecular dyes that coordinate with reporter gene-related bioluminescent phosphors for six-color fluorescence imaging.

Multicolor fluorescence microscopy for surgical guidance using a chip-scale imager with a low-NA fiber optic plate and a multi-bandpass interference filter.

In curative-intent cancer surgery, intraoperative fluorescence imaging of both diseased and healthy tissue can help to ensure the successful removal of all gross and microscopic diseases with minimal damage to neighboring critical structures, such as nerves. Current fluorescence-guided surgery (FGS) systems, however, rely on bulky and rigid optics that incur performance-limiting trade-offs between sensitivity and maneuverability. Moreover, many FGS systems are incapable of multiplexed imaging. As a result, clinical FGS is currently limited to millimeter-scale detection of a single fluorescent target. Here, we present a scalable, lens-less fluorescence imaging chip, VISION, capable of sensitive and multiplexed detection within a compact form factor. Central to VISION is a novel optical frontend design combining a low-numerical-aperture fiber optic plate (LNA-FOP) and a multi-bandpass interference filter, which is affixed to a custom CMOS image sensor. The LNA-FOP acts as a planar collimator to improve resolution and compensate for the angle-sensitivity of the interference filter, enabling high-resolution and multiplexed fluorescence imaging without lenses. We show VISION is capable of detecting tumor foci of less than 100 cells at near video framerates and, as proof of principle, can simultaneously visualize both tumors and nerves in ex vivo prostate tissue.

Thermal-plex: fluidic-free, rapid sequential multiplexed imaging with DNA-encoded thermal channels.

Multiplexed fluorescence imaging is typically limited to three- to five-plex on standard setups. Sequential imaging methods based on iterative labeling and imaging enable practical higher multiplexing, but generally require a complex fluidic setup with several rounds of slow buffer exchange (tens of minutes to an hour for each exchange step). We report the thermal-plex method, which removes complex and slow buffer exchange steps and provides fluidic-free, rapid sequential imaging. Thermal-plex uses simple DNA probes that are engineered to fluoresce sequentially when, and only when, activated with transient exposure to heating spikes at designated temperatures (thermal channels). Channel switching is fast (<30 s) and is achieved with a commercially available and affordable on-scope heating device. We demonstrate 15-plex RNA imaging (five thermal × three fluorescence channels) in fixed cells and retina tissues in less than 4 min, without using buffer exchange or fluidics. Thermal-plex introduces a new labeling method for efficient sequential multiplexed imaging.

Wide-field endoscope accessory for multiplexed fluorescence imaging

A wide-field endoscope that is sensitive to fluorescence can be used as an adjunct to conventional white light endoscopy by detecting multiple molecular targets concurrently. We aim to demonstrate a flexible fiber-coupled accessory that can pass forward through the instrument channel of standard medical endoscopes for clinical use to collect fluorescence images. A miniature scan mirror with reflector dimensions of 1.30 × 0.45 mm2 was designed, fabricated, and placed distal to collimated excitation beams at λex = 488, 660, and 785 nm. The mirror was driven at resonance for wide angular deflections in the X and Y-axes. A large image field-of-view (FOV) was generated in real time. The optomechanical components were packaged in a rigid distal tip with dimensions of 2.6 mm diameter and 12 mm length. The scan mirror was driven at 27.6 and 9.04 kHz in the fast (X) and slow (Y) axes, respectively, using a square wave with 50% duty cycle at 60 Vpp to collect fluorescence images at 10 frames per sec. Maximum total divergence angles of ± 27.4° and ± 22.8° were generated to achieve a FOV of 10.4 and 8.4 mm, respectively, at a working distance of 10 mm. Multiplexed fluorescence images were collected in vivo from the rectum of live mice using 3 fluorescently-labeled peptides that bind to unique cell surface targets. The fluorescence images collected were separated into 3 channels. Target-to-background ratios of 2.6, 3.1, and 3.9 were measured. This instrument demonstrates potential for broad clinical use to detect heterogeneous diseases in hollow organs.

Simultaneous visualization of multiple wavelengths by filter-free wavelength imaging system

This paper demonstrates the simultaneous imaging of multiple wavelengths through realizing a filter-free wavelength image sensor and imaging system. The sensor can identify the center wavelength of the spectrum based on the current ratio using the optical absorption characteristics of silicon at different wavelengths and the potential peak formed at depth. A wavelength imaging system was fabricated and calibrated by evaluating the light intensity and wavelength characteristics of each pixel. First, an experiment was conducted assuming that fluorescence was emitted in part of the pixel region of the image sensor. The system successfully identified different fluorescence wavelengths only in the region irradiated by light corresponding to the fluorescence using the current ratio. Finally, experiments were conducted using fluorescent beads on actual cells and pathogen clusters. Red and green fluorescent beads were placed separately on the sensor, and we succeeded in simultaneously imaging the wavelengths of the three regions where only the excitation light and different fluorescence signals were emitted. These results suggest that multiplexed fluorescence imaging, which considers the interactions between sites or targets, can provide new insights into the biomedical

Lactate biosensors for spectrally and spatially multiplexed fluorescence imaging

l-Lactate is increasingly appreciated as a key metabolite and signaling molecule in mammals. However, investigations of the inter- and intra-cellular dynamics of l-lactate are currently hampered by the limited selection and performance of l-lactate-specific genetically encoded biosensors. Here we now report a spectrally and functionally orthogonal pair of high-performance genetically encoded biosensors: a green fluorescent extracellular l-lactate biosensor, designated eLACCO2.1, and a red fluorescent intracellular l-lactate biosensor, designated R-iLACCO1. eLACCO2.1 exhibits excellent membrane localization and robust fluorescence response. To the best of our knowledge, R-iLACCO1 and its affinity variants exhibit larger fluorescence responses than any previously reported intracellular l-lactate biosensor. We demonstrate spectrally and spatially multiplexed imaging of l-lactate dynamics by coexpression of eLACCO2.1 and R-iLACCO1 in cultured cells, and in vivo imaging of extracellular and intracellular l-lactate dynamics in mice.

Near-infrared fluorescent probes for non-invasive, real-time, and dual-color in vivo NIR-II imaging

Multiplexed fluorescence imaging is mainly applied to cellular imaging. However, the application of an analogous technique to mammals remains challenging due to the presence of substantial scattering and autofluorescence in biological tissues in the visible (350–700 nm) and near-infrared I region (NIR-I, 700–900 nm). Herein, we report multiplexing excitation and single-channel detection in the near-infrared II region (NIR-II) with two fluorescent probes for dual-color imaging in vivo. The first one, FNIR-1090 was constructed on Pr-1099 derivative by attaching with 1-Ethylpiperazine through the SRN1 displacement reaction. The second one, IR-765 was synthesized by a one-step reaction between the Vilsmeier–Haack reagent with 2-(3,5,5-trimethylcyclohex-2-enylidene) malononitrile (TEMO). It is noteworthy that the absorption spectrum of FNIR-1090 is almost completely separated from that of IR-765, which facilitates dual-color in vivo imaging. The two dyes can be used for high-contrast dual-channel vivo imaging of different tissues. All these prominent performances show the great promise of FNIR-1090 and IR-765 in non-invasive, real-time, and dual-color NIR-II imaging (>900 nm) in vivo.

Systems approaches to characterize the local heterogeneities in NK cell antitumor immunity in MHC I-disparate human non-small cell lung cancer

Abstract Checkpoint immunotherapy has shown encouraging yet limited success in non-small cell lung cancer (NSCLC) patients. We combined multiplexed fluorescence imaging with quantitative spatial analysis to investigate antitumoral immunity in NSCLC. As seen before, we observed frequent MHC class I (MHC I) loss and development of CD8 T cell refractory tumors. MHC I-deficiency suggested NK cells may confer protection in NSCLC. Indeed, we found higher CD3 −CD56 +NK cell numbers were associated with both disease-free and overall survival. Using partial least squares regression, we found that both T cells and NK cells were significantly enriched in MHC I-bearing tumors. Quantitative spatial characterization of tumor cell MHC I expression revealed vast intra- and inter-tumoral heterogeneity, which was highly associated with the local lymphocyte landscape. To infer functional differences in local cell-cell communication, we built computational models based on spatial single cell neighborhood profiles to discriminate between IFNg-disparate lymphocytes. We found IFNg +NK cells more frequently associated with other IFNg +NK cells or T cells in comparison to IFNg −NK cells, or IFNg +T cells which more frequently had IFNg −lymphocyte neighbors. Moreover, IFNg +NK cells were unique in their capacity to also associate with MHC I −tumor cells. Together these data implicate a key role for NK cells in recruiting and activating other lymphocytes in MHC I-bearing tumors, and further suggest NK cells may be key to developing effective therapies even in CD8 T cell refractory tumors. Supported by UVA Carter Immunology Center Collaborative Research Award

NIR-II multiplexed fluorescence imaging of bacteria based on excitation-selective lanthanide-doped core-shell nanoparticles

Physiological processes and bacterial infection can be effectively monitored using multiplexed imaging in the second near-infrared region (NIR-II). In this study, we design two lanthanide-doped core-shell (cs) nanoparticles, NaYF4:Nd,Yb@NaYF4 (csNd,Yb) with 980 and 1060 nm emission under 808 nm excitation, and NaYF4:Yb,Er,Ce@NaYF4 (csYb,Er,Ce) with 1525 nm emission under 980 nm excitation. The NIR-II emission spectra of the two nanoparticles do not overlap. XRD characterization shows that the nanoparticles have good crystallinity. The nanoparticles are surface modified with vancomycin (Van) and polymyxin B (PMB), which can respectively target Gram-positive and Gram-negative bacteria for specific imaging and bacteria differentiation. In vitro experiments confirm that csNd,Yb-PMB and csYb,Er,Ce-Van can be used to detect different types of bacteria. In vivo simultaneous multiplexed NIR-II imaging of Gram-positive/negative bacterial infection is demonstrated. The good biocompatibility of the nanoprobes is demonstrated by MTT assay, monitoring the distribution in major organs at different times, and histological analysis.

Spatial immunophenotyping of the tumour microenvironment in non–small cell lung cancer

IntroductionImmune cells in the tumour microenvironment are associated with prognosis and response to therapy. We aimed to comprehensively characterise the spatial immune phenotypes in the mutational and clinicopathological background of non–small cell lung cancer (NSCLC). MethodsWe established a multiplexed fluorescence imaging pipeline to spatially quantify 13 immune cell subsets in 359 NSCLC cases: CD4 effector cells (CD4-Eff), CD4 regulatory cells (CD4-Treg), CD8 effector cells (CD8-Eff), CD8 regulatory cells (CD8-Treg), B-cells, natural killer cells, natural killer T-cells, M1 macrophages (M1), CD163+ myeloid cells (CD163), M2 macrophages (M2), immature dendritic cells (iDCs), mature dendritic cells (mDCs) and plasmacytoid dendritic cells (pDCs). ResultsCD4-Eff cells, CD8-Eff cells and M1 macrophages were the most abundant immune cells invading the tumour cell compartment and indicated a patient group with a favourable prognosis in the cluster analysis. Likewise, single densities of lymphocytic subsets (CD4-Eff, CD4-Treg, CD8-Treg, B-cells and pDCs) were independently associated with longer survival. However, when these immune cells were located close to CD8-Treg cells, the favourable impact was attenuated. In the multivariable Cox regression model, including cell densities and distances, the densities of M1 and CD163 cells and distances between cells (CD8-Treg–B-cells, CD8-Eff–cancer cells and B-cells–CD4-Treg) demonstrated positive prognostic impact, whereas short M2–M1 distances were prognostically unfavourable. ConclusionWe present a unique spatial profile of the in situ immune cell landscape in NSCLC as a publicly available data set. Cell densities and cell distances contribute independently to prognostic information on clinical outcomes, suggesting that spatial information is crucial for diagnostic use.

Integrated Cytometry With Machine Learning Applied to High-Content Imaging of Human Kidney Tissue for In Situ Cell Classification and Neighborhood Analysis

The human kidney is a complex organ with various cell types that are intricately organized to perform key physiological functions and maintain homeostasis. New imaging modalities, such as mesoscale and highly multiplexed fluorescence microscopy, are increasingly being applied to human kidney tissue to create single-cell resolution data sets that are both spatially large and multidimensional. These single-cell resolution high-content imaging data sets have great potential to uncover the complex spatial organization and cellular makeup of the human kidney. Tissue cytometry is a novel approach used for the quantitative analysis of imaging data; however, the scale and complexity of such data sets pose unique challenges for processing and analysis. We have developed the Volumetric Tissue Exploration and Analysis (VTEA) software, a unique tool that integrates image processing, segmentation, and interactive cytometry analysis into a single framework on desktop computers. Supported by an extensible and open-source framework, VTEA’s integrated pipeline now includes enhanced analytical tools, such as machine learning, data visualization, and neighborhood analyses, for hyperdimensional large-scale imaging data sets. These novel capabilities enable the analysis of mesoscale 2- and 3-dimensional multiplexed human kidney imaging data sets (such as co-detection by indexing and 3-dimensional confocal multiplexed fluorescence imaging). We demonstrate the utility of this approach in identifying cell subtypes in the kidney on the basis of labels, spatial association, and their microenvironment or neighborhood membership. VTEA provides an integrated and intuitive approach to decipher the cellular and spatial complexity of the human kidney and complements other transcriptomics and epigenetic efforts to define the landscape of kidney cell types.

Ultrabright AIEdots with tunable narrow emission for multiplexed fluorescence imaging.

AIEgen doped fluorescent nanodots (AIEdots) have attracted lots of attention, due to their superior characteristics as fluorescent probes, such as excellent photostability, large Stokes shift, high brightness and tunable emission. Unfortunately, most of the currently available AIEdots exhibit broad emission bandwidth, which limits their applications in multiplexed fluorescence imaging and detection. In this work, the strategy of designing and fabricating narrow emissive AIEdots (NE-AIEdots) with tunable wavelengths was presented by constructing a light-harvesting system with high energy transfer efficiency. Efficient intra-particle energy transfer from highly doped AIEgens, serving as the light-harvesting antenna, to the lightly doped narrow emissive fluorophore, resulted in high brightness and narrow emission. The emission band of NE-AIEdots with the full-width-at-half-maximum varied from 18 to 36 nm was 3-6.3 times narrower than that of traditional AIEdots. The single-particle brightness of NE-AIEdots was over 5-times that of commercial quantum dots under the same excitation and collection conditions. Taking advantage of the superior performance of these NE-AIEdots, multiplexed fluorescence imaging of lymph nodes in living mice was realized, which supported the future applications of NE-AIEdots for in vivo multiplexed labeling and clinical surgery.

A flexible open-source processing workflow for multiplexed fluorescence imaging based on cycles.

Background Multiplexing tissue imaging is developing as a complement for single cell analysis, bringing the spatial information of cells in tissue in addition to multiple parameters measurements. More and more commercial or home-made systems are available. These techniques allow the imaging of tens of fluorescent reporters, where the spectral overlap is solved by imaging by cycles the fluorophores using microfluidics to change the reporters between each cycle. Methods For several systems, the acquisition system coupled to the microfluidic system is a wide field microscope, and the acquisition process is done by mosaicking to cover a large field of view, relying on image processing to obtain the data set to be analysed in intensity. The processed data set allows the identification of different populations, quite similarly to cytometry analysis, but with spatial information in addition. To obtain the final image for analysis from the raw acquisitions, several preprocessing steps are needed for inter-cycle registration, tissue autofluorescence correction or mosaicking. We propose a workflow for this preprocessing, implemented as an open source software (as a library, command line tool and standalone). Results We exemplify the workflow on the commercial system PhenoCycler TM (formerly named CODEX®) and provide a reduced size data set for testing. Conclusions We compare our processor with the commercially provided processor and show that we solve some problems also reported by other users.

A real-time GPU-accelerated parallelized image processor for large-scale multiplexed fluorescence microscopy data.

Highly multiplexed, single-cell imaging has revolutionized our understanding of spatial cellular interactions associated with health and disease. With ever-increasing numbers of antigens, region sizes, and sample sizes, multiplexed fluorescence imaging experiments routinely produce terabytes of data. Fast and accurate processing of these large-scale, high-dimensional imaging data is essential to ensure reliable segmentation and identification of cell types and for characterization of cellular neighborhoods and inference of mechanistic insights. Here, we describe RAPID, a Real-time, GPU-Accelerated Parallelized Image processing software for large-scale multiplexed fluorescence microscopy Data. RAPID deconvolves large-scale, high-dimensional fluorescence imaging data, stitches and registers images with axial and lateral drift correction, and minimizes tissue autofluorescence such as that introduced by erythrocytes. Incorporation of an open source CUDA-driven, GPU-assisted deconvolution produced results similar to fee-based commercial software. RAPID reduces data processing time and artifacts and improves image contrast and signal-to-noise compared to our previous image processing pipeline, thus providing a useful tool for accurate and robust analysis of large-scale, multiplexed, fluorescence imaging data.

Multiplex imaging of human induced pluripotent stem cell-derived neurons with CO-Detection by indEXing (CODEX) technology

BackgroundHuman induced pluripotent stem cell (iPSC) models have been hailed as a breakthrough for understanding disease and developing new therapeutics. The major advantage of iPSC-derived neurons is that they carry the genetic background of the donor, and as such could be more predictive for clinical translation. However, the development of these cell models is time-consuming and expensive and it is thus critical to maximize readout of markers for immunocytochemistry. One option is to use a highly multiplexed fluorescence imaging assay, like CO-Detection by indEXing (CODEX), which allows detection of 50 + targets in situ. New methodThis paper describes the development of CODEX in neuronal cell cultures derived from human iPSCs. ResultsWe differentiated human iPSCs into mixed neuronal and glial cultures on glass coverslips. We then developed and optimized a panel of 21 antibodies to phenotype iPSC-derived neuronal subtypes of cortical, dopaminergic, and striatal neurons, as well as astrocytes, and pre-and postsynaptic proteins. Comparison with existing methodsCompared to standard immunocytochemistry, CODEX oligo-conjugated fluorophores circumvent antibody host interactions and allow for highly customized multiplexing. ConclusionWe show that CODEX can be applied to iPSC neuronal cultures and developed fixation and staining protocols for the neurons to sustain the multiple wash-stain cycles of the technology. Furthermore, we demonstrate both cellular and subcellular resolution imaging of multiplexed markers in the same sample.

CellSeg: a robust, pre-trained nucleus segmentation and pixel quantification software for highly multiplexed fluorescence images

BackgroundAlgorithmic cellular segmentation is an essential step for the quantitative analysis of highly multiplexed tissue images. Current segmentation pipelines often require manual dataset annotation and additional training, significant parameter tuning, or a sophisticated understanding of programming to adapt the software to the researcher’s need. Here, we present CellSeg, an open-source, pre-trained nucleus segmentation and signal quantification software based on the Mask region-convolutional neural network (R-CNN) architecture. CellSeg is accessible to users with a wide range of programming skills.ResultsCellSeg performs at the level of top segmentation algorithms in the 2018 Kaggle Data Challenge both qualitatively and quantitatively and generalizes well to a diverse set of multiplexed imaged cancer tissues compared to established state-of-the-art segmentation algorithms. Automated segmentation post-processing steps in the CellSeg pipeline improve the resolution of immune cell populations for downstream single-cell analysis. Finally, an application of CellSeg to a highly multiplexed colorectal cancer dataset acquired on the CO-Detection by indEXing (CODEX) platform demonstrates that CellSeg can be integrated into a multiplexed tissue imaging pipeline and lead to accurate identification of validated cell populations.ConclusionCellSeg is a robust cell segmentation software for analyzing highly multiplexed tissue images, accessible to biology researchers of any programming skill level.