Deep learning extended depth-of-field microscope for fast and slide-free histology.

Microscopic evaluation of resected tissue plays a central role in the surgical management of cancer. Because optical microscopes have a limited depth-of-field (DOF), resected tissue is either frozen or preserved with chemical fixatives, sliced into thin sections placed on microscope slides, stained, and imaged to determine whether surgical margins are free of tumor cells-a costly and time- and labor-intensive procedure. Here, we introduce a deep-learning extended DOF (DeepDOF) microscope to quickly image large areas of freshly resected tissue to provide histologic-quality images of surgical margins without physical sectioning. The DeepDOF microscope consists of a conventional fluorescence microscope with the simple addition of an inexpensive (less than $10) phase mask inserted in the pupil plane to encode the light field and enhance the depth-invariance of the point-spread function. When used with a jointly optimized image-reconstruction algorithm, diffraction-limited optical performance to resolve subcellular features can be maintained while significantly extending the DOF (200 µm). Data from resected oral surgical specimens show that the DeepDOF microscope can consistently visualize nuclear morphology and other important diagnostic features across highly irregular resected tissue surfaces without serial refocusing. With the capability to quickly scan intact samples with subcellular detail, the DeepDOF microscope can improve tissue sampling during intraoperative tumor-margin assessment, while offering an affordable tool to provide histological information from resected tissue specimens in resource-limited settings.

Pyrene Excimer-Based Fluorescent Labeling of Cysteines Brought into Close Proximity by Protein Dynamics: ASEM-Induced Thiol-Ene Click Reaction for High Spatial Resolution CLEM.

Fluorescence microscopy (FM) has revealed vital molecular mechanisms of life. Mainly, molecules labeled by fluorescent probes are imaged. However, the diversity of labeling probes and their functions remain limited. We synthesized a pyrene-based fluorescent probe targeting SH groups, which are important for protein folding and oxidative stress sensing in cells. The labeling achieved employs thiol-ene click reactions between the probes and SH groups and is triggered by irradiation by UV light or an electron beam. When two tagged pyrene groups were close enough to be excited as a dimer (excimer), they showed red-shifted fluorescence; theoretically, the proximity of two SH residues within ~30 Å can thus be monitored. Moreover, correlative light/electron microscopy (CLEM) was achieved using our atmospheric scanning electron microscope (ASEM); radicals formed in liquid by the electron beam caused the thiol-ene click reactions, and excimer fluorescence of the labeled proteins in cells and tissues was visualized by FM. Since the fluorescent labeling is induced by a narrow electron beam, high spatial resolution labeling is expected. The method can be widely applied to biological fields, for example, to study protein dynamics with or without cysteine mutagenesis, and to beam-induced micro-fabrication and the precise post-modification of materials.

LIVE-PAINT allows super-resolution microscopy inside living cells using reversible peptide-protein interactions.

We present LIVE-PAINT, a new approach to super-resolution fluorescent imaging inside live cells. In LIVE-PAINT only a short peptide sequence is fused to the protein being studied, unlike conventional super-resolution methods, which rely on directly fusing the biomolecule of interest to a large fluorescent protein, organic fluorophore, or oligonucleotide. LIVE-PAINT works by observing the blinking of localized fluorescence as this peptide is reversibly bound by a protein that is fused to a fluorescent protein. We have demonstrated the effectiveness of LIVE-PAINT by imaging a number of different proteins inside live S. cerevisiae. Not only is LIVE-PAINT widely applicable, easily implemented, and the modifications minimally perturbing, but we also anticipate it will extend data acquisition times compared to those previously possible with methods that involve direct fusion to a fluorescent protein.

Topical dual-probe staining using quantum dot-labeled antibodies for identifying tumor biomarkers in fresh specimens.

PURPOSE: Rapid, intra-operative identification of tumor tissue in the margins of excised specimens has become an important focus in the pursuit of reducing re-excision rates, especially for breast conserving surgery. Dual-probe difference specimen imaging (DDSI) is an emerging approach that uses the difference in uptake/clearance kinetics between a pair of fluorescently-labeled stains, one targeted to a biomarker-of-interest and the other an untargeted isotype, to reveal receptor-specific images of the specimen. Previous studies using antibodies labeled with either enhanced Raman particles or organic fluorophores have shown promising tumor vs. normal diagnostic performance. Yet, the unique properties of quantum dot-labeled antibody complexes (QDACs), which provide spectrally-distinct fluorescence emission from a common excitation source, make them ideal candidates for this application. Herein, we evaluate the diagnostic performance of QDAC-based DDSI in excised xenografts. PROCEDURES: Excised fresh specimens of normal tissue and human tumor xenografts with elevated expression of HER2 were stained with a HER2-targeted QDAC and an untargeted QDAC isotype. Stained specimens were imaged on a custom hyperspectral imaging system capable of spectrally separating the quantum dot signatures, and images processed using the DDSI approach. The diagnostic performance of this technique under different incubation temperatures and probe concentrations was evaluated using receiver-operator characteristic analysis. RESULTS: HER2-targeted QDAC-DDSI was able to distinguish HER2(+) tumors from normal tissue with reasonably high diagnostic performance; however, this performance was sensitive to temperature during the staining procedure. Area under the curve values were 0.61 when staining at room temperature but increased to over 0.81 when staining at 37 °C. Diagnostic performance was not affected by increasing stain concentration. CONCLUSIONS: This study is the first to report dual-probe difference imaging of specimens using QDACs and hyperspectral imaging. Our results show promising diagnostic performance under certain conditions, and compel further optimization and evaluation of this intra-operative margin assessment technique.

Quantitative accounting of dye leakage and photobleaching in single lipid vesicle measurements: Implications for biomacromolecular interaction analysis.

Highly parallel measurements on single, tethered lipid vesicles enable real-time monitoring of dynamic membrane interactions of relevance to medical, pharmaceutical, and biotechnological applications. Monitoring the time-dependent release of entrapped fluorescent dyes is a popular measurement approach, although it is often challenging to accurately extract quantitative biochemical parameters. Key issues include dye leakage and imaging-related photobleaching, and corrective measures are needed. Herein, we present an extended analytical framework to collect and interpret time-lapsed fluorescence microscopy imaging data, and demonstrate its utility for tracking membrane-peptide interactions. Our approach is focused on improving platform design and data analysis. First, we identified suitable membrane compositions to minimize dye leakage while enhancing the biomimetic character of lipid vesicles. Second, a data normalization procedure was developed to correct for experimental artifacts, namely dye leakage and photobleaching, and hence improve measurement accuracy. This analytical procedure was applied to experimentally determine the rate of peptide-induced pore formation in single lipid vesicles, and there was up to a nearly three-fold decrease in the measured rate, as compared to uncorrected data. Taken together, the results present a broadly applicable analytical framework to account for experimental artifacts and improve measurement accuracy in highly parallel, single lipid vesicle arrays.

Yellow-emissive carbon dots with a large Stokes shift are viable fluorescent probes for detection and cellular imaging of silver ions and glutathione.

Yellow-emissive carbon dots (Y-CDs) were prepared by a solvothermal method using anhydrous citric acid and 2,3-phenazinediamine as the starting materials. The Y-CDs display a 24% fluorescence quantum yield, a 188-nm Stokes' shift and excellent stability. They are shown here to be excellent fluorescent probes for the determination of Ag(I) ion and glutathione (GSH). If exposed to Ag(I) ions, they are bound by the carboxy groups of the Y-CDs, and this causes quenching of fluorescence (with excitation/emission maxima at 380/568 nm) via a static quenching mechanism. This effect was used to design a fluorometric assay for Ag(I). The quenched fluorescence of the Y-CDs can be restored by adding GSH due to the high affinity of GSH for Ag(I). The calibration plot for Ag(I) is linear in the 1-4 µM Ag(I) concentration range, and the limit of detection is 31 nM. The respective values for GSH are 5-32 µM, and 76 nM, respectively. The method was applied to the detection of Ag(I) in spiked environmental water samples and gave recoveries ranging from 93 to 107%. It was also applied to the determination of GSH in tomatoes and purple grapes and gave satisfactory recoveries. The Y-CDs display low cytotoxicity and were successfully used to image Ag(I) and GSH in H1299 cells. Graphical abstract Schematic presentation of the mechanism of yellow fluorescent CDs for the detection of Ag+ and glutathione.

Super-resolution fluorescence microscopy studies of human immunodeficiency virus.

Super-resolution fluorescence microscopy combines the ability to observe biological processes beyond the diffraction limit of conventional light microscopy with all advantages of the fluorescence readout such as labelling specificity and non-invasive live-cell imaging. Due to their subdiffraction size (< 200 nm) viruses are ideal candidates for super-resolution microscopy studies, and Human Immunodeficiency Virus type 1 (HIV-1) is to date the most studied virus by this technique. This review outlines principles of different super-resolution techniques as well as their advantages and disadvantages for virological studies, especially in the context of live-cell imaging applications. We highlight the findings of super-resolution based HIV-1 studies performed so far, their contributions to the understanding of HIV-1 replication cycle and how the current advances in super-resolution microscopy may open new avenues for future virology research.

Challenges for Super-Resolution Localization Microscopy and Biomolecular Fluorescent Nano-Probing in Cancer Research.

Understanding molecular interactions and regulatory mechanisms in tumor initiation, progression, and treatment response are key requirements towards advanced cancer diagnosis and novel treatment procedures in personalized medicine. Beyond decoding the gene expression, malfunctioning and cancer-related epigenetic pathways, investigations of the spatial receptor arrangements in membranes and genome organization in cell nuclei, on the nano-scale, contribute to elucidating complex molecular mechanisms in cells and tissues. By these means, the correlation between cell function and spatial organization of molecules or molecular complexes can be studied, with respect to carcinogenesis, tumor sensitivity or tumor resistance to anticancer therapies, like radiation or antibody treatment. Here, we present several new applications for bio-molecular nano-probes and super-resolution, laser fluorescence localization microscopy and their potential in life sciences, especially in biomedical and cancer research. By means of a tool-box of fluorescent antibodies, green fluorescent protein (GFP) tagging, or specific oligonucleotides, we present tumor relevant re-arrangements of Erb-receptors in membranes, spatial organization of Smad specific ubiquitin protein ligase 2 (Smurf2) in the cytosol, tumor cell characteristic heterochromatin organization, and molecular re-arrangements induced by radiation or antibody treatment. The main purpose of this article is to demonstrate how nano-scaled distance measurements between bio-molecules, tagged by appropriate nano-probes, can be applied to elucidate structures and conformations of molecular complexes which are characteristic of tumorigenesis and treatment responses. These applications open new avenues towards a better interpretation of the spatial organization and treatment responses of functionally relevant molecules, at the single cell level, in normal and cancer cells, offering new potentials for individualized medicine.

Combining Low Temperature Fluorescence DNA-Hybridization, Immunostaining, and Super-Resolution Localization Microscopy for Nano-Structure Analysis of ALU Elements and Their Influence on Chromatin Structure.

Immunostaining and fluorescence in situ hybridization (FISH) are well established methods for specific labelling of chromatin in the cell nucleus. COMBO-FISH (combinatorial oligonucleotide fluorescence in situ hybridization) is a FISH method using computer designed oligonucleotide probes specifically co-localizing at given target sites. In combination with super resolution microscopy which achieves spatial resolution far beyond the Abbe Limit, it allows new insights into the nano-scaled structure and organization of the chromatin of the nucleus. To avoid nano-structural changes of the chromatin, the COMBO-FISH labelling protocol was optimized omitting heat treatment for denaturation of the target. As an example, this protocol was applied to ALU elements-dispersed short stretches of DNA which appear in different kinds in large numbers in primate genomes. These ALU elements seem to be involved in gene regulation, genomic diversity, disease induction, DNA repair, etc. By computer search, we developed a unique COMBO-FISH probe which specifically binds to ALU consensus elements and combined this DNA-DNA labelling procedure with heterochromatin immunostainings in formaldehyde-fixed cell specimens. By localization microscopy, the chromatin network-like arrangements of ALU oligonucleotide repeats and heterochromatin antibody labelling sites were simultaneously visualized and quantified. This novel approach which simultaneously combines COMBO-FISH and immunostaining was applied to chromatin analysis on the nanoscale after low-linear-energy-transfer (LET) radiation exposure at different doses. Dose-correlated curves were obtained from the amount of ALU representing signals, and the chromatin re-arrangements during DNA repair after irradiation were quantitatively studied on the nano-scale. Beyond applications in radiation research, the labelling strategy of immunostaining and COMBO-FISH with localization microscopy will also offer new potentials for analyses of subcellular elements in combination with other specific chromatin targets.

Benchmarking of fluorescence cameras through the use of a composite phantom.

Fluorescence molecular imaging (FMI) has shown potential to detect and delineate cancer during surgery or diagnostic endoscopy. Recent progress on imaging systems has allowed sensitive detection of fluorescent agents even in video rate mode. However, lack of standardization in fluorescence imaging challenges the clinical application of FMI, since the use of different systems may lead to different results from a given study, even when using the same fluorescent agent. In this work, we investigate the use of a composite fluorescence phantom, employed as an FMI standard, to offer a comprehensive method for validation and standardization of the performance of different imaging systems. To exclude user interaction, all phantom features are automatically extracted from the acquired epi-illumination color and fluorescence images, using appropriately constructed templates. These features are then employed to characterize the performance and compare different cameras to each other. The proposed method could serve as a framework toward the calibration and benchmarking of FMI systems, to facilitate their clinical translation.

Multiscale image analysis reveals structural heterogeneity of the cell microenvironment in homotypic spheroids.

Three-dimensional multicellular aggregates such as spheroids provide reliable in vitro substitutes for tissues. Quantitative characterization of spheroids at the cellular level is fundamental. We present the first pipeline that provides three-dimensional, high-quality images of intact spheroids at cellular resolution and a comprehensive image analysis that completes traditional image segmentation by algorithms from other fields. The pipeline combines light sheet-based fluorescence microscopy of optically cleared spheroids with automated nuclei segmentation (F score: 0.88) and concepts from graph analysis and computational topology. Incorporating cell graphs and alpha shapes provided more than 30 features of individual nuclei, the cellular neighborhood and the spheroid morphology. The application of our pipeline to a set of breast carcinoma spheroids revealed two concentric layers of different cell density for more than 30,000 cells. The thickness of the outer cell layer depends on a spheroid's size and varies between 50% and 75% of its radius. In differently-sized spheroids, we detected patches of different cell densities ranging from 5 × 105 to 1 × 106 cells/mm3. Since cell density affects cell behavior in tissues, structural heterogeneities need to be incorporated into existing models. Our image analysis pipeline provides a multiscale approach to obtain the relevant data for a system-level understanding of tissue architecture.

High-resolution microendoscopy: a point-of-care diagnostic for cervical dysplasia in low-resource settings.

Cervical cancer is the third leading cause of cancer-related death among women in low-to-middle income countries. Pap testing and pathological services are difficult to implement under these settings. Alternative techniques for the diagnosis of cervical precancer in these settings are needed to reduce the burden of the disease. The objective of this study was to evaluate the diagnostic accuracy of a low-cost, high-resolution microendoscope imaging system in identifying precancerous lesions of the cervix in vivo. A retrospective study of 59 patients undergoing colposcopy for an abnormal Pap test was performed at Hospital de Câncer de Barretos in Brazil. All patients underwent colposcopy as per standard of care, and acetowhite lesions were recorded. High-resolution microendoscopy (HRME) images were obtained from one colposcopically normal region and from all lesions observed on colposcopy. Biopsies of abnormal areas were obtained and reviewed by three independent, blinded pathologists and compared with HRME findings. The mean nuclear area and the median nuclear eccentricity were calculated from HRME images acquired from each site. A diagnostic algorithm to distinguish histopathologically diagnosed cervical intraepithelial neoplasias of grade 2 or more severe lesions (high grade) from less severe lesions (low grade) was developed using these parameters. A test of trend was used to analyze the relationship between HRME positivity and severity of histopathogical diagnosis. Fisher's exact test was used to analyze differences in HRME positivity between high-grade and low-grade lesions. Evaluable images were obtained from 108 of 143 discrete sites. Of these, 71 sites were colposcopically normal or low grade according to histopathology and 37 were diagnosed as high grade on the basis of histopathology. Using the mean nuclear area and the median nuclear eccentricity, HRME images from 59 colposcopically abnormal sites were classified as high grade or low grade with 92% sensitivity and 77% specificity compared with histopathological findings. Increasing HRME positivity showed a significant trend with increasing severity of diagnosis (Ptrend<0.001). We found a strong association (P<0.001) between HRME positivity and a histopathological diagnosis of cervical intraepithelial neoplasia of grade 2 or higher. HRME demonstrated an accurate in-situ diagnosis of high-grade dysplasia. In low-resource settings in which colposcopy and histopathology services are severely limited or unavailable, HRME may provide a low-cost, accurate method for diagnosis of cervical precancer without the need for biopsy, allowing for a single 'screen-and-treat' approach.

Ultra-sensitive detection of tumorigenic cellular impurities in human cell-processed therapeutic products by digital analysis of soft agar colony formation.

Contamination with tumorigenic cellular impurities is one of the most pressing concerns for human cell-processed therapeutic products (hCTPs). The soft agar colony formation (SACF) assay, which is a well-known in vitro assay for the detection of malignant transformed cells, is applicable for the quality assessment of hCTPs. Here we established an image-based screening system for the SACF assay using a high-content cell analyzer termed the digital SACF assay. Dual fluorescence staining of formed colonies and the dissolution of soft agar led to accurate detection of transformed cells with the imaging cytometer. Partitioning a cell sample into multiple wells of culture plates enabled digital readout of the presence of colonies and elevated the sensitivity for their detection. In practice, the digital SACF assay detected impurity levels as low as 0.00001% of the hCTPs, i.e. only one HeLa cell contained in 10,000,000 human mesenchymal stem cells, within 30 days. The digital SACF assay saves time, is more sensitive than in vivo tumorigenicity tests, and would be useful for the quality control of hCTPs in the manufacturing process.

High-resolution in-depth imaging of optically cleared thick samples using an adaptive SPIM.

Today, Light Sheet Fluorescence Microscopy (LSFM) makes it possible to image fluorescent samples through depths of several hundreds of microns. However, LSFM also suffers from scattering, absorption and optical aberrations. Spatial variations in the refractive index inside the samples cause major changes to the light path resulting in loss of signal and contrast in the deepest regions, thus impairing in-depth imaging capability. These effects are particularly marked when inhomogeneous, complex biological samples are under study. Recently, chemical treatments have been developed to render a sample transparent by homogenizing its refractive index (RI), consequently enabling a reduction of scattering phenomena and a simplification of optical aberration patterns. One drawback of these methods is that the resulting RI of cleared samples does not match the working RI medium generally used for LSFM lenses. This RI mismatch leads to the presence of low-order aberrations and therefore to a significant degradation of image quality. In this paper, we introduce an original optical-chemical combined method based on an adaptive SPIM and a water-based clearing protocol enabling compensation for aberrations arising from RI mismatches induced by optical clearing methods and acquisition of high-resolution in-depth images of optically cleared complex thick samples such as Multi-Cellular Tumour Spheroids.

Automated Classification of Circulating Tumor Cells and the Impact of Interobsever Variability on Classifier Training and Performance.

Application of personalized medicine requires integration of different data to determine each patient's unique clinical constitution. The automated analysis of medical data is a growing field where different machine learning techniques are used to minimize the time-consuming task of manual analysis. The evaluation, and often training, of automated classifiers requires manually labelled data as ground truth. In many cases such labelling is not perfect, either because of the data being ambiguous even for a trained expert or because of mistakes. Here we investigated the interobserver variability of image data comprising fluorescently stained circulating tumor cells and its effect on the performance of two automated classifiers, a random forest and a support vector machine. We found that uncertainty in annotation between observers limited the performance of the automated classifiers, especially when it was included in the test set on which classifier performance was measured. The random forest classifier turned out to be resilient to uncertainty in the training data while the support vector machine's performance is highly dependent on the amount of uncertainty in the training data. We finally introduced the consensus data set as a possible solution for evaluation of automated classifiers that minimizes the penalty of interobserver variability.

The use of FLIM-FRET for the detection of mitochondria-associated protein interactions.

Fluorescence lifetime imaging microscopy-Förster resonant energy transfer (FLIM-FRET) is a high-resolution technique for the detection of protein interactions in live cells. As the cost of this technology becomes more competitive and methods are devised to extract more information from the FLIM images, this technique will be increasingly useful for studying protein interactions in live cells. Here we demonstrate the use of the ISS-Alba FLIM/FCS confocal microscope, which was custom-built for supervised automation of FLIM data acquisition. We provide a detailed protocol for collecting and analyzing good FLIM-FRET data. As an example, we use FLIM-FRET to detect the interaction between BclXL and Bad at the mitochondrial outer membrane in live MCF7 breast cancer cells.

A computational platform for robotized fluorescence microscopy (II): DNA damage, replication, checkpoint activation, and cell cycle progression by high-content high-resolution multiparameter image-cytometry.

Dissection of complex molecular-networks in rare cell populations is limited by current technologies that do not allow simultaneous quantification, high-resolution localization, and statistically robust analysis of multiple parameters. We have developed a novel computational platform (Automated Microscopy for Image CytOmetry, A.M.I.CO) for quantitative image-analysis of data from confocal or widefield robotized microscopes. We have applied this image-cytometry technology to the study of checkpoint activation in response to spontaneous DNA damage in nontransformed mammary cells. Cell-cycle profile and active DNA-replication were correlated to (i) Ki67, to monitor proliferation; (ii) phosphorylated histone H2AX (γH2AX) and 53BP1, as markers of DNA-damage response (DDR); and (iii) p53 and p21, as checkpoint-activation markers. Our data suggest the existence of cell-cycle modulated mechanisms involving different functions of γH2AX and 53BP1 in DDR, and of p53 and p21 in checkpoint activation and quiescence regulation during the cell-cycle. Quantitative analysis, event selection, and physical relocalization have been then employed to correlate protein expression at the population level with interactions between molecules, measured with Proximity Ligation Analysis, with unprecedented statistical relevance.

A computational platform for robotized fluorescence microscopy (I): high-content image-based cell-cycle analysis.

Hardware automation and software development have allowed a dramatic increase of throughput in both acquisition and analysis of images by associating an optimized statistical significance with fluorescence microscopy. Despite the numerous common points between fluorescence microscopy and flow cytometry (FCM), the enormous amount of applications developed for the latter have found relatively low space among the modern high-resolution imaging techniques. With the aim to fulfill this gap, we developed a novel computational platform named A.M.I.CO. (Automated Microscopy for Image-Cytometry) for the quantitative analysis of images from widefield and confocal robotized microscopes. Thanks to the setting up of both staining protocols and analysis procedures, we were able to recapitulate many FCM assays. In particular, we focused on the measurement of DNA content and the reconstruction of cell-cycle profiles with optimal parameters. Standard automated microscopes were employed at the highest optical resolution (200 nm), and white-light sources made it possible to perform an efficient multiparameter analysis. DNA- and protein-content measurements were complemented with image-derived information on their intracellular spatial distribution. Notably, the developed tools create a direct link between image-analysis and acquisition. It is therefore possible to isolate target populations according to a definite quantitative profile, and to relocate physically them for diffraction-limited data acquisition. Thanks to its flexibility and analysis-driven acquisition, A.M.I.CO. can integrate flow, image-stream and laser-scanning cytometry analysis, providing high-resolution intracellular analysis with a previously unreached statistical relevance.

A position paper on standardizing the nonneoplastic kidney biopsy report.

The biopsy report for nonneoplastic kidney diseases represents a complex integration of clinical data with light, immunofluorescence, and electron microscopic findings. Practice guidelines for the handling and processing of the renal biopsy have previously been created. However, specific guidelines for essential pathologic parameters that should be included in these pathology reports do not exist. The Renal Pathology Society has coordinated an effort through the formation of an ad hoc committee to enumerate the essential elements and pathologic parameters that should be reported for every biopsy specimen. This endeavor aims to establish a minimum reporting standard and to improve communication between pathologists and other physicians. This document represents the collective effort and consensus opinions of this ad hoc committee of the Renal Pathology Society.

Dark pixel intensity determination and its applications in normalizing different exposure time and autofluorescence removal.

The purpose of this study is to investigate how to scale pixel intensity acquired from one exposure time to another. This is required when comparing grayscale images acquired at different exposure times and other image processing such as autofluorescence removal. Pixel intensity is linear to exposure time as long as images are acquired at the linear range of a camera, but importantly there exists an intercept, which is set by the camera. We termed this intercept as dark pixel intensity, as it is the pixel intensity under conditions of no light and zero exposure time. Dark pixel intensity is determined by camera's readout noise (electron/pixel), gain, and DC offset. Knowing dark pixel intensity, image acquired from one exposure time can be linearly scaled to an image at a different exposure time. Dark pixel intensity can be directly measured by obtaining an image at no light and zero (or minimum) exposure time. It can be also indirectly calculated by capturing images at a series of exposure times. Finally, the prestained and poststained images were acquired at their optimal exposures and autofluorescence was completely removed by normalizing images with the exposure time ratio and dark pixel intensity followed by subtraction.