NEWS
20. January 2025
In the rapidly evolving field of medical diagnostics and research, AI-powered tissue classification emerges as a transformative technology.
Read More15. January 2025
The specific characteristics of individual cells can only offer so much detail during analysis or categorization.
Read More22. October 2024
On 13th of November, join us for a joint webinar with the experts from TissueGnostics and CrestOptics for more insight into imaging and image analysis.
Register here...22. October 2024
Can you believe that there are around 30-40 trillion cells in the human body alone? Each has their own purpose and structure that help them to undertake their day-to-day tasks.
Read More16. July 2024
Through the power of spatial phenotyping, we gain the ability to shine a spotlight on different cell types and their environments.
Read More03. July 2024
The field of cytometry has witnessed significant advancements with the introduction of tissue cytometry and high-throughput cytometers, revolutionizing tissue analysis.
Read More15. May 2024
Felix Tsai, TG-AP Business Manager, shared an article featuring TLS as a key player in cancer and solutions to invesigate them.
Read here...06. May 2024
Histopathology, a cornerstone of pathological diagnosis, is undergoing a transformation thanks to advancements in imaging technologies.
Read More25. March 2024
Artificial Intelligence (AI) has emerged as a transformative force in numerous disciplines. This includes imaging cytometry.
Read More18. March 2024
The eRaDicate consortium consists of eight academic and one industrial beneficiaries, as well as 13 associated partners to develop new therapies against cancer stem cell-driven relapse and metastasis.
... Read More19. February 2024
In research and clinical diagnosis, tissue microarrays (TMA) have become a standard technique.
Read More12. February 2024
Understanding the interactions of cellular, multi-cellular, and non-cellular components that make up our tissues is an important foundation of medical research.
Read More22. November 2023
Planet TV Studios present TissueGnostics GmbH and its day-to-day operations discussing topics of business in science with Dr. Rupert Ecker, CEO TissueGnostics, as well as portraying what scientists using TissueGnostics' solutions have to say.
… Watch hereNovember 13, 2023
In biomedical research, techniques like immunofluorescence staining combined with tissue cytometry have emerged as powerful tools for studying cellular structures, protein expression, and interactions in-situ within tissue samples. These techniques provide valuable insights into cellular function and
… Read More10. November 2023
Rupert Ecker, Asia / Pacific Managing Director Wu Hai and Scientist Jyotsna Batra of the Translational Research Institute of the Queensland University of Technology, Australia gave an interview for Medianet discussing business in science.
… Watch hereNovember 8, 2023
Precision medicine is a rapidly growing field in healthcare that aims to provide personalized treatment and care to patients based on their individual medical history. This approach has the potential to revolutionize the way we think about healthcare
… Read More31. October 2023
We are glad to share exciting news: TissueGnostics Global welcomes our newest family member – TissueGnostics Australia Pty Ltd! The new subsidiary was founded in October 2023 and is located in Brisbane, Queensland.
...Read MoreOctober 23, 2023
Tissue samples are highly complex in their structure. This complexity makes screening samples for signs of immune modulation as a result of disease and for understanding new therapeutic pathways a very challenging task, but one that offers a
… Read MoreOctober 9, 2023
Image-based cytometry is rapidly revolutionizing tissue analysis. It is a technique that combines fluorescent microscopy and features of conventional flow cytometry to rapidly characterize individual cell populations in the native tissue environment. This process provides valuable insights into cell characteristics
… Read More11. September 2023
Dr. Rupert Ecker, the distinguished CEO of TissueGnostics, has achieved a remarkable milestone by gracing the cover of the 𝙒𝙤𝙧𝙡𝙙’𝙨 𝙇𝙚𝙖𝙙𝙚𝙧𝙨 𝙈𝙖𝙜𝙖𝙯𝙞𝙣𝙚.
...Read More06. September 2023
Dr. Rupert Ecker, CEO TissueGnostics, was nominated as one of the most impactful leaders in healthcare in 2023 by The CIO Today journal.
...Read More30. August 2023
Multiplexing combines multiple measurements in a single experiment. In tissue cytometry, multiplexing involves using multiple fluorophores that emit at different wavelengths or even multiple de-/staining rounds and thereby increase the number of markers that can be visualized.
… Read More27. June 2023
TissueGnostics was nominated as Company of the Year by HealthCare Insights magazine. Dr. Rupert Ecker, CEO of TissueGnostics, also gave an interview about company's history and future outlooks.
...Read MoreJune 26, 2023
High-content phenotyping is one of the key tools in establishing genotype-to-phenotype links and understanding the degree of plasticity a particular phenotype has. 1 There are some thoughts that phenotypic plasticity may play a role in the development
… Read More21. June 2023
We are delighted to be featured in the new article of Medical Tech Outlook! Dr. Rupert Ecker, CEO of TissueGnostics, talks about the use of computational microscopy in the pathology field in the interview for the journal.
… Read More12. June 2023
The study correlated xCT activity in HNSCC cancer samples within the cell with patient survival rates to determine whether this molecule can serve as a potential therapeutic target in HNSCC patients.
… Read MoreMay 17, 2023
Modern microscopy methods can provide an overwhelming amount of information in a single experiment. With multiwavelength emissive probes and enhanced 3D or Z stack imaging capabilities, image analysis in biomedical imaging has become an increasingly complex and
… Read More24. April 2023
Dr. Rupert Ecker, CEO of TissueGnostics, and Dr. Jyotsna Batra, QUT, participated in publishing a book on cancer genetics as co-guest editors. The book covers methods and new insights in cancer biology and is available for free to read.
… Read MoreApril 19, 2023
Spheroids, organoids and embryoid bodies are highly valuable 3D culture techniques that are widely used in research for all different kinds of applications. Combined with biomedical imaging and image analysis, those 3D cultures can give
… Read More04. Apr 2023
Glioma is the most common type of malignant brain tumor and is associated with high morbidity and mortality. To better understand the relationship between phenotype and transcript-level changes in glioma, the team looked at
… Read More28. March 2023
Dr. Rupert Ecker, CEO of TissueGnostics, participated in the interview for Insightscare Magazine, where he talks about company's history and future insights.
...Read More15. March 2023
The European Doctoral Network ‘SSBB’ is offering a PhD position in the area of ‘novel antimicrobial approaches to combat multidrug-resistant bacteria’, which will start in June 2023.
Apply hereMarch 6, 2023
There are a multitude of methods to study tumor immunology such as qPCR, FACS, or in-situ stainings of tissue sections. Tissue microarrays (TMA) are small tissue sections used in research and clinics for the analysis of all
… Read More13. February 2023
Nadine Bayer, PhD , presents her paper “Disturbances in microbial skin recolonization and cutaneous immune response following allogeneic stem cell transfer”, which was recently published in the high-impact journal Stem Cell Transplantation.
… Watch hereFebruary 6, 2022
Fluorescence in-situ hybridization (FISH) is a cytology method that uses a hybridizing DNA probe and either direct or indirect labeling to detect genes of interest or genetic abnormalities in cells resulting from gene fusion or an
… Read More30. January 2023
TG is a member of the Euro BioImaging Industry Board - on the the Africa Microscopy Initiative (AMI) funded by Chan Zuckerberg Initiative and the Melinda and Bill Gates Foundation. Read more below.
... Read here23. January 2023
TissueGnostics is pleased to announce that we have become a new associated company of the Brazilian Society of Microscopy and Microanalysis (SBMM). Read more about the goals of the partnership below.
.... Read hereJanuary 23, 2023
Cytometry encompasses several methods for investigating cells, such as their count, cell cycle state, phenotype, morphology, size etc. The main goal of cytometry is to characterize individual cells. Although flow cytometry is frequently used to obtain this data, the
… Read More15. February 2023
Cell segmentation is a method for quantifying the number of cells within a tissue section or a given area. Cell segmentation is the basis of all tissue cytometry analyses, including FISH/CISH/RNAscope detection, in-depth phenotyping, and spatial analysis. Therefore, accurate
… Read MoreJanuary 18, 2023
Advanced and robust in-situ hybridization techniques are required to study the genetics of cell and molecular biology both accurately and efficiently. Fluorescence in-situ hybridization – abbreviated FISH – was developed to enable researchers to analyze the genetics of cells by
… Read More12. December 2022
In the article for Eurolab magazine, Anastasiia Marchuk and Felicitas Mungenast (TG) discuss how tissue cytometry can help to unravel the complexity of cellular populations in the tissue environment. Read the artcile to know more about present applications.
… Read here28. November 2022
Acquisition, management, dissemination, and interpretation of pathology data, including data and slides, are all included in digital pathology. Whole tissue samples are acquired using slide scanners to produce digital slides, which are high-resolution digital images that
… Read More08. November 2022
ELMI organisators talk about the international ELMI (European Light Microscopy Initiative) conference, where TissueGnostics team also took part in, and impressions of participants from it.
... Read here08. November 2022
Prof. Nicolas C. Hoch, University of Sao Paulo, is presenting his research on signaling and repair of DNA damage, utilizing the power of TissueFAXS i PLUS slide scanning and the high-end image analysis solution, StrataQuest.
… Watch here19. October 2022
The research facility at MedUni Vienna's Centre for Pathophysiology, Infectiology and Immunology has thus been recognised by TissueGnostics as a global leader in the use of this technology, known as the TissueFAXS platform.
.... Read hereOctober 19, 2022
Cell counting underpins much of biomedical research. Yet it is a complex process that requires sophisticated computer technology to yield accurate results in a time efficient manner. To do so, scientists rely on artificial intelligence, such as machine learning, to
… Read More12. October 2022
One novel approach in cancer treatment is to target the anti or pro tumoral immune response.It has been reported that CD103+CD39+CD8+ TRM cells are present at higher levels in CRLM
… Read MoreOctober 12, 2022
The process of cell counting is important to biomedical research as it can reveal valuable information about single cells, populations of cells, and cell dynamics and further it is the basis of more sophisticated tissue cytometry workflows.
… Read MoreSeptember 28, 2022
Visualization of tissue samples in biomedical research is necessary for drawing informative conclusions. Imaging techniques are valuable in providing this visualization, especially on microscales that are difficult to characterize and quantify without powerful technology.
The in-depth study of cellular
… Read MoreSeptember 19, 2022
Powerfully advanced techniques are required to determine the properties of special cellular subpopulations in their native tissue environment. Mass cytometry is one such technology, allowing the identification of cellular phenotypes with antibody markers for further analysis. Two types of recent
… Read MoreSeptember 1, 2022
The context through which biomedical scientists analyze cellular phenotypes within tissues determines the type of information that will come out of the laboratory. Spatial biology is one such context in which biological studies can be conducted and is particularly impactful in
… Read More22. August 2022
Dr. Rupert Ecker, CEO of TissueGnostics, gives a short introduction of TissueGnostics’ tissue cytometry solutions with the main focus on immunophenotyping and spatial analysis of the tumor microenvironment in situ.
Watch here29. June 2022
Biomedicine relies heavily on understanding the immune system on a microscopic level. Specifically, regarding cancer treatments, the investigation into the tumor immune microenvironment is paramount in developing effective new treatment strategies for the debilitating disease. The tumor immune microenvironment includes
… Read More27. June 2022
Dr. Thomas Diefenbach, The Ragon Institute Boston, presents various approaches for multiplexing IF, utilizing the power of TissueFAXS high-throughput automated slide scanning and StrataQuest powered high-end image analysis.
...Watch here15. June 2022
The appearance of a novel human coronavirus (SARS-CoV-2) in 2019 resulted in a global pandemic that caused social and economic devastation worldwide. Infection with SARS-CoV-2 has a highly heterogenous presentation.
… Read MoreJune 8, 2022
Histology, or the study of tissues, is a valuable realm of research that underpins a plethora of biomedical innovations today. Much of the work in life sciences relies on biological samples such as tissues in
… Read More25. May 2022
Tissues, representing an interactive community of various cell types, underpin much of biomedical and health research and can give an important insight into development, progress and therapy of diseases. Performing tissue microenvironment analysis, to dissect cellular components and their interactions,
… Read More17. May 2022
In the special edition of Trillium Diagnostik journal Dr. Felicitas Mungenast and Alexander Stickler-Barang discuss the importance of immunophenotyping in tissue sections for the diagnosis of various diseases. The arcticle is available in German.
...Read More13. May 2022
Researchers have attempted to tackle COVID-19 from various angles. One of the most useful and impactful ways in which biomedical scientists investigate the disease is through studies on the immune system. Immunity studies provide information directly applicable
… Read More11. May 2022
Dr. T. Diefenbach in his zoom webinar discusses the work he and his colleagues conducted at the Ragon Insitute in Boston where the dynamics of
… Read More4. May 2022
One of the challenges of imaging tissue sections is dealing with their diverse composition. The human body contains hundreds of different cell phenotypes, with many more to be discovered.
... Read More21. April 2022
Image cytometry is a method that uses imaging as well as image analysis to extract quantitative information from stained cells/tissues. Image cytometry is frequently used alongside flow cytometry and provides deep insight of cell/tissue morphology and cell-cell interactions whilst
… Read More13. April 2022
As the AI hype in the life science industry slowly fades away, AI technologies have formed a solid basis for current solutions and future developments. Experts from TG’s global network discuss in the new Dossier
… Read More10. February 2022
Cutaneous leishmaniasis (CL) caused by infection with the Leishmania protozoan is endemic in Sri Lanka. The disease is transmitted by the sandfly and causes widespread burden due to the social stigma causing sufferers to be
… Read More25. January 2022
The digitization of stained tissue samples, the visual analysis and communication of data involving disease research and clinics through digital mediums is referred to as digital pathology. It can be
… Read More07. December 2021
What is multispectral flow cytometry?
Multispectral flow cytometry is an analytical technique that allows the measurement of fluorescence or Raman spectra from individual cells in suspension. Building on the technology used in conventional flow cytometry, multispectral cytometry deals with a spectral
09. November 2021
Histopathology is the scientific branch focusing on assessment of diseases by examining stained biological tissue sections, particularly in human subjects. This field can give immense insight into biological and medical areas of study. With advancing technology and innovative capabilities, laboratories can
… Read More03. November 2021
This was a collaborative webinar series with PreciPoint GmbH focusing on AI assisted image analysis. The purpose of this webinar series is to explain AI software to new and upcoming AI
… Watch here25. October 2021
Colorectal cancer is uncontrolled and is therefore pathological cell growth originating either within the colon or rectum of the body. One of the most common types of cancer, colorectal cancer, made up almost 2 million new diagnoses
… Read More14. October 2021
High resolution microscopy relies heavily on efficient confocal slide scanners to accurately and speedily image markers/target components within cells. Confocal slide scanners ensure high resolution visualization of fluorescent biomarkers within cell and tissue structures, a crucial technique in biomedical
… Read More07. October 2021
Dr. Axel Dievernich (RWTH Aachen) presents the results of his recently published paper. It addresses the characterization of the adaptive and innate immune cells involved in foreign human body reaction.
… Watch here04. October 2021
Surgery, chemotherapy and radiation have formed the mainstay of cancer therapy for many years. However, in addition to destroying tumor cells, these treatments are detrimental to healthy cells giving rise to side effects, which can be severe.
… Read More30. September 2021
TG is hosting together with Precipoint an exiting webinar series entitled "From Tissue Classification to Proximity Measurement". The purpose of this webinar series is to explain AI software to new and upcoming AI users in the context of pathology research.
… Sign Up for Part 121. September 2021
Recently Delacher and colleagues were able to redefine the transcriptional and epigenetic signature of tissue-associated regulatory T cells (Treg) in mice and humans (Delacher et al. 2021). They could demonstrate, that Treg
… Read More20. September 2021
The next iteration of the TissueFAXS suite (7.1) has arrived. Discover all the new optimizations in TissueFAXS imaging software and exciting new AI features in StrataQuest , TissueQuest , and HistoQuest.
… Read More15. September 2021
Alex Barang, responsible for International Sales & Business Development at TissueGnostics, contributed recently to an Biocompare editorial about 'Automation in Multiplexing'.
... Read More09. September 2021
Dr. Gregory CG Hugenholtz, Deptartment of Surgery, University Medical Center Groningen, talks about "TAFI deficiency promotes liver damage in murine models of liver failure through defective down-regulation of hepatic inflammation". TissueGnostics brightfield
… Watch here07. September 2021
TissueGnostics is proud to announce a new member of the TissueFAXS series, the TissueFAXS CHROMA. This system specializes in automated multispectral fluorescence whole slide scanning for up to 7 markers at a time. This cost-effective high-speed slide scanner reaches its
… Read More15. July 2021
Whole slide imaging, sometimes known as virtual microscopy or digital pathology, involves the scanning of a tissue section on a slide to create a digital reconstruction of the entire tissue section by stitching the single fields of view together.
… Read More06. July 2021
Surgical mesh is used in a range of tissue repair procedures to stabilize and strengthen soft tissue defects or to support prolapsed organs and viscera. One of their most common applications is hernia
… Read More TissueGnostics GmbH
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The IF Skeletal Muscle App allows the segmentation of skeletal muscle tissue sections into muscle fibers and connective tissue based on specific IF staining. Outcome parameters are provided, such as the number of muscle fibers and area of the total tissue, muscle fibers, and connective tissue.
Image: Courtesy of Stefania Petrini, Bambino Gesù Children’s Hospital, Rome
App Category 2
The IHC Adipocyte App quantifies adipocytes and their lumen in adequate HE samples. The App automatically mends small rips in adipocyte membranes and eliminates cell membrane artifacts in adipocyte lumina and lumina on sample borders. The App also outputs area measurements for all detected adipocyte lumina.
App Category 1
The IF 2 App provides single cell-based co-expression analysis for two IF markers. It segments cells into their nucleus, perinuclear area, and/or cytoplasm. Each segmented cell compartment is measured for up to 20 intensity, statistic, and morphometric parameters that can be displayed in and exported into scattergrams and histograms.
App Category 1
The IF 3 App provides single cell-based co-expression analysis for three IF markers. It segments cells into their nucleus, perinuclear area, and/or cytoplasm. Each segmented cell compartment is measured for up to 20 intensity, statistic, and morphometric parameters that can be displayed in and exported into scattergrams and histograms.
App Category 1
The IF 4 App provides single cell-based co-expression analysis for four IF markers. It segments cells into their nucleus, perinuclear area, and/or cytoplasm. Each segmented cell compartment is measured for up to 20 intensity, statistic, and morphometric parameters that can be displayed in and exported into scattergrams and histograms.
App Category 2
The IF Glomeruli App provides the detection of tissue, cells, and glomeruli stained by a specific marker. It segments the cells into their nucleus and/or cytoplasm and determines the cellular phenotype of specific IF-stained cell populations. The detected cells can be classified as being either inside or outside the glomeruli within certain distances (distance ranges are definable). For each cell, the spatial information and up to 20 intensity, statistics, and morphometric parameters are measured. The data can be displayed in diagrams and exported.
App Category 3
The IF Hi-Plex 50 App combines and analyses images of the same IF-stained tissue section, acquired up to 50 times with different markers. The App enables the detection of the cellular phenotypes of specific IF-stained cell populations. It segments cells into their nucleus, perinuclear area, and/or cytoplasm. Each segmented cell compartment is measured for up to 20 intensity, statistic, and morphometric parameters that can be displayed in and exported into scattergrams and histograms.
App Category 3
The IF Dots App provides dot detection per cell within the cell compartments for up to four markers in a sample (e.g., FISH, RNA, oil droplets). Each segmented cell compartment is measured for up to 20 intensity, statistic, and morphometric parameters. Dot measurement parameters are provided per cell compartment (e.g., nucleus, cytoplasm) and per dot and include count, mean intensity, total dot area, the sum of intensity.
App Category 2
The IF Immune Status in Situ App provides a phenotypic characterization of immune cells in reference to detected metastructures (e.g., tumors, glands) and measures the distance of detected cellular objects to the metastructure boundary (within and/or outside). Distance ranges are also definable. Each segmented cell compartment is measured for up to 20 intensity, statistic, and morphometric parameters, as well as the distance of each cell to the areas boundary.
App Category 3
The IF Skin Morphology App provides tissue detection, including the segmentation of epidermis and dermis, based on specific IF staining. It segments cells into their nucleus, perinuclear area, and/or cytoplasm and determines the cellular phenotype of specific IF-stained cell populations. The detected cells can be classified and visualized as being within or outside detected structures (epidermis and dermis). Each segmented cell compartment is measured for up to 20 intensity, statistic, and morphometric parameters that can then be displayed in diagrams and exported.
App Category 3
The IF Granuloma App detects granulomas based on nuclear structure analysis and an adequate IF staining (e.g., CD11c, CD68). The App measures the number and area of Granulomas and their density. Each segmented cell compartment is measured for up to 20 intensity, statistic, and morphometric parameters.
App Category 2
The IF Cytoskeleton App detects cytoskeletal structures based on a specific stain. The cell cytoplasm can be detected using other stains. Data can also be exported, including the number of cytoskeletal filaments inside and outside the cell and on the cell membrane, filament length, and total filament area.
App Category 3
The IF Glial Cells App allows the detection of astrocytes and microglia based on specific IF staining. The measurements assessed by the App include the number of astrocytes and microglia and the number of branches of each cell (short and long attached).
App Category 3
The IHC 2 App unmixes two markers (e.g., chromogen and counterstain) in an IHC or HC digital slide and segments single cells into their nucleus, perinuclear area, and/or cytoplasm. Each segmented cell compartment is measured for up to 20 intensity, statistic, and morphometric parameters that can be displayed in and exported into scattergrams and histograms.
App Category 1
The IHC 3 App unmixes three markers (e.g., two chromogens and a counterstain) in an IHC or HC digital slide and segments single cells into their nucleus, perinuclear area, and/or cytoplasm. Each segmented cell compartment is measured for up to 20 intensity, statistic, and morphometric parameters that can be displayed in and exported into scattergrams and histograms.
App Category 2
The IHC Macrophages App detects macrophages based on adequately stained IHC samples. The App can be combined with area detection and distance range algorithms to determine the distance of Langerhans cells from the border of the epidermis inside and outside the epidermis (see above example). Each segmented cell compartment is measured for up to 20 parameters, as is the distance of each cell to the boundary.
App Category 3
The IHC Tumor-Stroma App combines the segmentation of tumor and stroma (based on the morphology) and the detection of specifically stained cell populations. It segments the cells into their nucleus, perinuclear area, and/or cytoplasm. Each segmented cell compartment in tumor and/or stroma is measured for up to 20 intensity, statistic, and morphometric parameters that can be displayed in and exported into scattergrams and histograms.
App Category 2
The Pulmo App segments nuclei and the metastructure components of the lung, including tissue, bronchioles, blood vessels, and alveoles. Each segmented metastructure is measured for up to 20 morphometric parameters.
App Category 3
The IHC Angio App detects blood vessels based on appropriate stains (e.g., CD31) and measures overall vessel and lumen areas. The vessel detection can be set to close open stained vessel walls and connect separated vessel sections within a definable distance. As well as vessel number, density, and areas, the App also outputs endothelium and lumina areas.
App Category 2
The IHC Meta Cells App combines the detection of IHC/HC stained metastructures (e.g., Langerhans islets, Tumor - Stroma) with single-cell detection (segmentation of cells into nucleus, perinuclear area, and/or cytoplasm). Detected cells can be classified and visualized as being within or outside detected metastructures. Each detected area and cell compartment is measured for up to 20 intensity, statistic, and morphometric parameters.
App Category 2
The RNA Scope App enables the detection of nuclei based on appropriate staining and dot detection per cell within nucleus and/or cytoplasm for one dot marker in CISH and SISH experiments . Each segmented cell compartment is measured for up to 20 intensity, statistic, and morphometric parameters. Dot parameters are provided per cell and per dot and include count, mean intensity, total dot area and the sum of intensity.
App Category 2
The Tumor Foci App allows for the detection of the whole tissue and, more importantly, tumor foci based on nuclear structure analysis, mainly on HE staining. The number, area, and density of tumor foci are measured.
App Category 1
The IHC Membrane App unmixes up to three markers in an IHC or HC digital slide and segments cells into nucleus, perinuclear area, and/or cytoplasm, as well as into membrane (e.g., HER2/neu). Each segmented cell compartment is measured for up to 20 intensity, statistic, and morphometric parameters. Three more parameters are measured for membrane intensity and angle of staining. All parameters are displayed in scattergrams and histograms and can be exported.
App Category 2
The Bone Tissue Analysis Goldner App allows for the detection of mineralized bone tissue and osteoid based on Goldner-stained bone tissue sections. The App assesses parameters such as BV (bone volume), TV (trabecular bone volume), OV (osteoid volume), OV/BV, OV/TV, OS (osteoid surface), BS (bone surface length), and the mean of osteoid width and thickness.
App Category 2
The Bone Mineralization APP separates Safranin O-stained bone tissue into its morphological substructures (cartilage, mineralized cartilage, bone marrow, and mineralized bone). Measurements assessed with this App include TV (trabecular bone volume), BV (total bone volume), MCV (mineralized cartilage), CV (cartilage volume), and bone marrow (BM).
App Category 3
The Bone Tissue Analysis Von Kossa App allows for the detection of mineralized bone tissue based on Von Kossa stained bone tissue sections. The App provides parameters such as TV (trabecular bone volume), BV (bone volume), BS (bone surface), BV/TV, BS/BV, Tb.N (trabecular number), tb.Th (trabecular thickness), and Tb.Sp (trabecular separation).
App Category 2
The IF Leishmaniasis App detects intracellular Leishmania parasites and segments them in the detected host cells. The number of parasites per cell is determined, and living and dead parasites can be distinguished (live/dead assays). The App outputs 20 intensity, statistic, and morphometric parameters for each segmented cell compartment per marker, as well as the number, mean intensity, sum of intensity, and size of parasites.
App Category 2
The IF Cellular Microenvironment App allows to determine the cellular phenotype of specific IF-stained cell populations and establishes their spatial relationship between each other and their neighboring cells/cell populations, including those with metastructures (e.g., blood vessels, tumors) in their vicinity. It is especially suited for proximity and infiltration analyses.
App Category 4
The IF Neurite App identifies neuronal cells and cell clusters and their neurites/dendrites. It quantifies the number of neurites/dendrites branching out from a specific neuron, identifies branch points, and exports total neurite/dendrite area, total neurite/dendrite length, average neurite/dendrite thickness, the number of branch points, and the number of endpoints.
App Category 3
The IF Pyknotic Nuclei App provides tissue detection and cell segmentation in combination with the detection of pyknotic nuclei (defined as completely condensed, round, high-intensity nuclei) based on nuclei staining. Additionally, the App allows for the determination of the cellular phenotype of specific IF-stained cell populations and dot detection. It segments the detected cells into nucleus, perinuclear area, and/or cytoplasm. The App provides parameters such as the number, mean intensity, and percentage of specific cell populations (including cells containing pyknotic nuclei). It also outputs dot parameters per segmented cell and/or dot, including count, mean intensity, total dot area, and sum of intensity.
App Category 3
The IF Tumor Vascularization App provides tissue detection, including the separation of tumor tissue and tumor stroma (healthy tissue). Additionally, it detects blood vessels based on appropriate stains (e.g., CD31) and measures the number, area, and density of these blood vessels. The vessel detection also can be set to close open stained vessel walls and to connect separated vessel sections within a definable distance.
App Category 3
The IHC Tumor-Macrophages App provides tissue detection, including the separation of tumor and healthy tissue. It detects macrophages based on specific staining (e.g., CD68) and outputs the area of macrophages within tumor and healthy tissue.
Image: Courtesy of Dr. Patrick Michl, Dr. Maren Egidi, and Dr. Heidi Griesmann, Universitätsklinikum Halle (Saale).
App Category 3
The IHC Tumor Vascularization App provides tissue detection, including the separation of tumor tissue and tumor stroma (healthy tissue). Additionally, it detects blood vessels based on appropriate stains (e.g., CD31) and measures the number and area of these blood vessels. The vessel detection can also be programmed to close open stained vessel walls and to connect separated vessel sections within a definable distance. The App outputs the number, density, and areas of vessels within both tumor and healthy tissue.
Image: Courtesy of Dr. Patrick Michl, Dr. Maren Egidi, and Dr. Heidi Griesmann, Universitätsklinikum Halle (Saale).
App Category 3
The IHC Angio Trichome App detects blood vessels based on trichome staining and measures the overall vessel and lumen area. Furthermore, it detects specifically IHC-stained single cell populations and establishes their spatial relationship to the detected blood vessels. The App outputs number and vessel density, vessel wall thickness and areas of vessels, endothelium and lumina, the number of IHC stained cells, proximity measurement, etc.
App Category 3
The RNA Scope+ App provides detection of nuclei based on appropriate staining and dot detection per cell within the nucleus and/or cytoplasm for two dot markers in CISH and SISH experiments. Each segmented cell compartment is measured for up to 20 intensity, statistic, and morphometric parameters. It also outputs dot parameters per segmented cell and/or dot, including count, mean intensity, total dot area, and sum of intensity.
App Category 2
The IHC Angio Elastin App detects blood vessels in Verhoeffs van Geison-stained samples, elastin, and collagen. The outputs include the number and area of vessels, elastin, and collagen within a definable distance to the vessel.
App Category 2
The IF Cardio Cell Culture App provides cell segmentation, detection of cardiomyocytes (based on appropriate staining, e.g., Troponin Red), fibroblasts within cultured cardio cells, plus one additional marker. The App outputs parameters such as the number of cardiomyocytes, fibroblasts, and marker-positive cardiomyocytes and fibroblasts.
Image: Courtesy of Agatha Ribeiro da Silva, Prof. Jose E. Krieger (Heart Institute, University Sao Paulo)
App Category 3
The IF Cardio Cell Culture Dot App provides cell segmentation and detection of cardiomyocytes (based on an appropriate stain, e.g., Troponin Red) and fibroblasts within cultured cardio cells, plus one dot marker (CISH, FISH). The App outputs parameters such as the number of cardiomyocytes and fibroblasts. It also outputs the number of dot-positive cardiomyocytes and fibroblasts and the number, area (μm²), and mean intensity of dots per cell.
Image: Courtesy of Agatha Ribeiro da Silva, Prof. Jose E. Krieger (Heart Institute, University Sao Paulo).
App Category 3
The IF Dendrites & Axons App identifies neuronal cells, their dendrites and axon, based on appropriate markers. It quantifies the number of dendrites branching out from a specific neuron. The App provides the total number of dendrites per neuron, including the length of these dendrites and their axons.
Image: Courtesy of Thomas Bastian, Ph.D., University of Minnesota.
App Category 3
The IHC Small Intestine - Dots App provides nuclei segmentation and detection of tissue and villi based on nuclei staining (crypts need to be defined manually). Furthermore, it allows dot detection for one dot markers (CISH, RNAScope, SISH) within villi and crypt areas. Dot parameters are provided for villi and crypts and for dots and include count, mean intensity, total dot area, the sum of intensity.
App Category 2
The Lipid Droplets App quantifies lipid droplets within H&E stained tissues (e.g., liver). The App automatically mends small rips in liver droplet membranes and eliminates cell membrane artifacts, including lumina on sample borders. The App also outputs area and number measurements for all detected lipid droplets.
App Category 1
The Angio Sirius Red App detects collagen and blood vessels based on Sirius Red staining. The app outputs the area of Sirius Red stained collagen and the number of detected vessels.
App Category 2
The IHC Angio Diameter App detects blood vessels based on appropriate stains (e.g., CD31). The App outputs vessel area, number, density, and blood vessel diameter.
App Category 2
The IF Cultured Cells & Substructures App detects cells based on nuclei staining, as well as one dot marker (FISH, CISH experiments) and cytoskeletal structures based on a specific stain. It outputs the number of detected cells, the number and intensity of dots per cell, and the density of cytoskeletal filaments.
App Category 3
The IF Membrane App detects nuclei and segments the cells into different cellular compartments, including membrane, nuclei, and cytoplasm. It also detects one additional marker (e.g., HER2/neu). Each segmented cell compartment is measured for different parameters, such as staining intensity, stained area, and the number/percentage of marker-positive cells within the detected cellular compartments. Three more parameters are measured for the membrane, including membrane area, membrane length, and the angle of staining.
App Category 2
The IF Spheroids App allows a comprehensive analysis of spheroids (as well as organoids and embryoid bodies). It automatically identifies the spheroids and cells based on the nuclei staining and analyzes two additional IF markers. It segments the cells into different cellular compartments, including membrane, nuclei, and cytosol, and further measures the marker expression for each compartment. It can also measure dot markers (if available). It establishes proximity distances for the cells detected within the spheroids, bringing the IF-stained cell populations into spatial context.
App Category 3
The IHC Immune Status in Situ App uses the AI classifier to segment tissue into morphological entities such as tumor, stroma, and lymphocyte clusters. It further identifies single cells based on nuclei staining (hematoxylin), detects immune cells based on appropriated stains (CD45, CD3, CD20, etc.), and measures the distance of detected cells to the metastructure boundary. The App can also define distance ranges through outputting parameters, including the area of the detected morphological entities and the number/percentage of lymphocytes detected within the tissue entities, as well as in certain proximities.
App Category 3
The Wilms Tumor App is based on the AI Classifier and allows for the segmentation of H&E stained Wilms tumor tissues into tumor, stroma, and blood vessels. It outputs the area (µm2) of the segmented tissue entities.
App Category 1
The IHC Necrotic Tumor App segments tumor tissues into tumor, necrotic tissue, and stroma using the AI Classifier. Furthermore, it identifies single cells as well as one additional cellular marker (e.g., neutrophils). It outputs the area of tumor, necrotic tissue, and stroma and measures the number and percentage of neutrophils within the morphological entities.
App Category 3
The IHC Necrotic Tumor Angio App can segment tumor tissues into tumor, necrotic tissue, and blood vessels using the AI Classifier. It outputs the area of tumor, necrotic tissue, and blood vessels, as well as the number and percentage of blood vessels in total and within the two morphological entities.
App Category 3
The IF Rods & Cones in Retina App detects the rods and cones based on specific staining. It outputs the number, density, and length of detected structures, as well as the number, percentage, and density of marker-stained rods and cones.
App Category 2
The IF Tumor Foci Angio App identifies single cells and segments tissues into tumor foci and blood vessels based on appropriate markers. It applies proximity maps to identify nuclei close to blood vessels. It measures the number of nuclei located within a certain distance relative to blood vessels, the number of nuclei in the different morphological entities, and the area of these morphological entities.
App Category 3
The IF Retinal Vasculature App detects blood vessels in retinal tissue based on appropriate stains (e.g., CD31). The App outputs vessel area, density, and length.
App Category 2
The Endometrium HE App allows for the segmentation of hematoxylin and eosin-stained endometrium tissues into their morphological entities (glands, stroma, and blood vessels). The measurements provided by the App include the area of glands, stroma, and blood vessels.
App Category 2
The IHC Extracellular Filament App detects nuclei and extracellular filaments stained with specific markers. It outputs the number of nuclei, total filaments area, and the length of these filaments.
App Category 2
The IF Cellular Contact App allows for the determination of the cellular phenotype of specific IF-stained cell populations and establishes the cellular contacts to their neighboring cells (the number of markers is technically unlimited). If needed, the App provides a separation of nuclei in tissues with high cellular densities. The App outputs parameters such as staining intensity per marker and morphometric parameters for each segmented cell/cell compartment, as well as the number and percentage of cells of different phenotypes in direct contact.
Images: courtesy of Naoki Kaneko/Shiv Pillai (PI), Ragon Institute of MGH, MIT and Harvard, Boston, MA USA.
App Category 3
The App was used in a CELL publication, read more
The EBER-ISH App analyzes tissue samples stained by EBER-ISH probes (EBV-encoded RNA in-situ hybridization). These probes visualize the Epstein-Barr virus (EBV) EBER RNA. First, the App identifies nuclei, then detects EBER-ISH positive nuclei. The measurements provided by the App include the number of detected cells and the number, density, and percentage of EBER-ISH positive cells.
App Category 1
The IF Cell Culture - Osteoclast App allows for the segmentation of nuclei, the identification of cultured multinucleated osteoclasts (stained by a specific marker), and the quantification of one or two additional markers. Outputs include the number of detected cells, osteoclasts, and nuclei per osteoclast, the area of osteoclasts, and the intensity of markers within the osteoclasts.
App Category 2
read more about Automated Detection and Characterization of Osteoclasts in Microscopic Images
The Organoid App detects cultured organoids using the machine learning classifier. It outputs number and total area (µm2) of organoids and categorizes them into different size classes.
App Category 3
The IF Brain App allows the classification (using the AI based classifier) of brain regions and detection of various cellular phenotypes, e.g. astrocytes, based on stained linage markers. The App outputs area (µm2) of detected tissues classes, count of total cells as well as in each detected area. Count and % of specific phenotype detected in total as well as in tissue classes.
App Category 3
The Embryoid Bodies App automatically detects embryoid bodies/organoids based on IF staining. It identifies nuclei based on DAPI staining or other nuclei dye and identifies additional phenotype markers in the nuclei/cell and/or membrane of the detected cells. It outputs number and area (µm2) of detected embryoid bodies/organoids, count of nuclei and count/% of cellular phenotypes.
App Category 2
The IF Insulin Islet App allows for detection marker stained insulin islets, the whole tissue, and cellular phenotypes stained by specific markers within the insulin islets. The App outputs, whole tissue area (µm2), number and area (µm2) of detected insulin islets. Number of cells and marker-specific phenotypes in the whole tissue as well as within the insulin islets. Image provided by Emma Hamilton-Williams.
App Category 3
The Mucin Swiss Roll App allows for detection of the swiss roll, and the segmentation into different subclasses (mucosa, immune cell follicles, connective tissue, background). Further it detects nuclei and (e.g. PAS stained) mucin. The App outputs area (µm2) of detected tissues/tissue classes, count of total cells and in each detected area as well as the area of stained mucin in the entire tissue and within the subclasses. Image Courtesy: Priv.-Doz.Dr. Martin Schepelmann
App Category 2
The IHC Swiss Roll App allows for detection of the swiss roll, and the segmentation into different subclasses (mucosa, immune cell follicles, connective tissue, background). Further it detects nuclei and identifies phenotypes based on specific stains. The App outputs area (µm2) of detected tissues/tissue classes, count of total cells as well as in each detected area. Count and % of specific phenotype detected in total as well as in the tissue classes. Image Courtesy: Priv.-Doz.Dr. Martin Schepelmann
App Category 2
The IF Swiss Roll App allows for detection of the swiss roll, and the segmentation into different subclasses (mucosa, immune cell follicles, connective tissue, background). Further it detects nuclei and identifies phenotypes based on specific IF stains. The App outputs area (µm2) of detected tissues/tissue classes, count of total cells as well as in each detected area. Count and % of specific phenotype detected in total as well as in the tissue classes. Image Courtesy: Priv.-Doz.Dr. Martin Schepelmann
App Category 2
The IHC Insulin Islet App allows for detection of marker stained insulin islets, the whole tissue, and cellular phenotypes stained by specific markers within the insulin islets and in the tissue. The App outputs, whole tissue area (µm2), number and area (µm2) of detected insulin islets. Number of cells and marker-specific phenotypes in the whole tissue as well as within the insulin islets.
App Category 2
The IHC Adipocytes+ App identifies adipocytes and cellular aggregates inbetween the adipocytes. Small rips in adipocyte membranes are mended automatically and cell membrane artefacts in adipocyte lumina are automatically eliminated. The App outputs number and area measurements for all detected adipocytes as well as number and area of cellular aggregates.
App Category 2
The IHC Microglia App detects microglia soma based on a specifc staining and further identifies branches as well as primary and secondary branching points. It outputs number and area of cells, number of primary and secondary branching points as well as area and lenght of the detected branches.
App Category 3
The IHC Lung Cancer mouse App is using the machine learning base classifier to segment murine lung cancer tissue sections into tumor and non-cancerous tissue. Further it detects nuclei based on hematoxylin staining and identifies cellular phenotypes based on speicifc markers. It outputs number and area of tumor tissue as well as total number of cells and detected cellular phenotypes.
App Category 3
The IHC Megakaryocytes App allows for detection of megakaryocytes based on specific marker staining. It outputs number and size of detected megakaryocytes as well as the number of megakaryocytes that contain neutrophils inside their cytoplasm and the number of neutrophils inside each megakaryocyte. Image courtesy: Prof Wendy Erber and A/Prof Kathy Fuller, The University of Western Australia
App Category 2