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Imaris for Cancer Research is an ideal package for researchers who want to visualise their microscopy data and study tumor samples in cell cultures, spheroids or tissues. For time-lapse datasets Imaris for Cancer Research offers excellent tracking algorithms including cell division events and integrated tools to plot all measurements synchronised with cell divisions.
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Imaris enables visualization and virtual dissection of 3D data. Imaris for Cancer Research includes a variety of spatial interaction measurements, such as: distribution of objects around a Surface, shortest distance, volume overlap and nearest neighbour analysis. All measurements are highly reproducible and can be performed in the batch mode (automatically repeat the same analysis protocol for multiple samples) to save valuable time on the analysis.
At certain stages of searching for and evaluating new cancer therapies, whether it’s a chemotherapy, immunotherapy or radiotherapy, cell cultures or spheroids, researchers pick fluorescence microscopy to visualize the subtle and dynamic interaction and changes in the system. Imaris can directly open and visualize microscopy datasets in all formats available in the market. Imaris offers unique segmentation/object detection tools (like Spots and Surfaces) to better visualize and understand the sample in 3D.
Imaris for Cancer Research includes a seamlessly integrated tool to explore differences between experimental groups (e.g. control vs test) - ImarisVantage. It allows for the creation of interactive plots which help illustrate relationships/patterns/differences amongst object measurement or groups of objects and reveal hidden relationships.
Image visualisation and segmentation are just the first step of the in-depth image analysis in Imaris. With Imaris for Cancer Research Package you can do many more, including motion analysis, machine learning or statistics based object classification, measure interactions between objects or do that all on a large number of samples in a batch mode. Each analysis eventually leads to creation of an analytical plot showing the dependencies between your objects.
With Imaris 11, you can effortlessly create a customized image analysis protocol (Workflow) tailored to your specific research area and requirements. These Workflows can be saved and applied to other datasets with just one click, streamlining your analysis process. Discover how Workflows can accelerate your journey from microscopy data to meaningful insights, impactful publications, and engaging conference presentations.
The software supports a range of imaging workflows, from exploratory visualisation to advanced quantification and tracking. Its modular structure allows users to apply relevant tools depending on their experimental needs.
Imaris combines segmentation, tracking, and quantification within a single environment. This reduces reliance on multiple tools and supports consistent data analysis. It helps improve reproducibility across cancer research studies.
The platform supports analysis of complex interactions between cells within tumour environments. This allows researchers to study spatial relationships and dynamic behaviours. It is important for understanding tumour progression and response to treatment.
Imaris enables tracking of individual cells and populations over time. This supports analysis of migration, invasion, and proliferation. Tracking tools help quantify changes in behaviour within tumour systems.
Cell Biology is areas of research in life sciences that focus on the fundamental processes of life. Cell biology encompasses a broad range of research areas and applications such as apoptosis, cell cycle & cell division, DNA damage, plant cell biology, vesicle trafficking, in vitro studies etc. As for model organisms, cell biology investigates them all, from the most simple prokaryotes (bacteria) to single-cell eukaryotes (yeast, fungus) and even multicellular organisms.
Basic cancer research combines several aspects of studying cancer cell phenotypes, gene expression and interactions with the microenvironment in vitro and in vivo to better understand carcinogenesis, malignancy and develop new potential therapies. Cancer research often requires applying advanced fluorescence microscopy to study cancer cell behaviour interaction with the environment and spatial distribution of the tumour models in a time lapse.
Developmental Biology are areas of research in life sciences that focus on the fundamental processes of life. Developmental biology studies the process by which multicellular organisms grow and develop. Research focuses on processes such: as metamorphosis, embryonic development, tissue growth, morphogenesis, stem cell differentiation, embryogenesis, plant development and regeneration. Research in these areas is done both on a microscopic and molecular level, and multiple technologies are needed to successfully accomplish this work.
Neuroscience is a multidisciplinary branch of science focused on the study of the nervous system and how the brain works. The field studies nervous system functions, brain function and the related structures such as the spinal cord. It combines anatomy, physiology, cytology, molecular biology, developmental biology and modelling in order to understand neurons and neuronal circuits. As neuroscientists often balance on the cutting edge of science, they require sophisticated methods such as fluorescence labelling, optogenetics, photostimulation and state of the art image analysis.
Automated classification of cancer cells, immune cells or cell nuclei with a trainable Machine Learning Classifier (ML), based on selected statistic or the combination of 2 features. Classes are labelled and available for visual presentation, plotting and for downstream analysis (export of statistics). Classification and labelling of objects are batchable.
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