HALO AI | Trainable AI for Pathology - Indica Labs

Unlock Limitless Possibilities with HALO AI

HALO AI has you covered. Whether you’re looking to solve image analysis challenges in segmentation, classification, or phenotyping, the advanced deep learning networks of HALO AI are easily tuned for your specific application with the train-by-example interface.

Diverse and Powerful AI

Underpinned by modern deep learning networks, HALO AI provides a collection of segmentation, classification, and phenotyping tools for brightfield and fluorescence applications. Train a classifier to quantify tissue classes, to find rare events or cells in tissues, or to categorize cell populations into specific phenotypes.

AI-Powered Annotation

Use a point and click workflow to rapidly annotate images and develop training data.

Nuclear Segmentation

Choose between several trainable AI-based nuclear segmentation networks to optimize segmentation accuracy when nuclear morphologies vary.

Membrane Segmentation

Train AI-powered membrane segmentation networks to accurately delineate cell membranes for your specific assay.

Tissue Segmentation

Train AI-based MiniNet and DenseNet networks to classify tissue into user-defined classes.

Cell & Object Phenotyping

Quickly train a phenotyper to quantify cell types or objects of interest.

Slide Quality Control

Leverage a trainable AI-powered quality control network to detect common artifacts in H&E and IHC images.

Simple & Intuitive Workflow

HALO AI is fully integrated with the intuitive, easy-to-use HALO® and HALO Link platforms and employs a simple three-step workflow. After defining tissue classes or cell phenotypes, you train the neural network by drawing annotations – no computer programming or AI knowledge required.

Define Classes

Train Network

Apply Classifier

Choose to integrate your trained HALO AI networks in multiple locations within HALO modules to perform functions including tissue classification, nuclear and membrane segmentation, and phenotyping. Alternatively, apply HALO AI directly to an entire study of whole slide images or to select regions of interest – the choice is yours.

Manage Variability

Extreme variability runs rife in image analysis but is no match for HALO AI. Common sources of variability include diverse morphologies, alterations of morphologies from staining protocols, differences in tissue quality, uneven staining, and more.

HALO AI can be easily trained to accommodate variability to deliver accurate segmentation and classification results across large studies. HALO AI can even be trained to work across vastly different stains such as PAMS, Trichrome, H&E, and IHC.

Exceptional Identification

Pre-trained nuclear and membrane segmentors available in HALO are advanced tools for nuclear and membrane segmentation, but when you need to optimize a network for a bespoke application, you need HALO AI.

As with the tissue classification and segmentation networks, you can quickly add training data with the AI-based annotation tool and train the network to optimally segment nuclei or cell membranes. And once trained, any HALO AI network can be incorporated into HALO modules for maximum utility.

Powerful Tissue Classification

The degree of variability encountered in pathology often demands an approach above and beyond a simple random forest tissue classifier.

HALO AI has two advanced pre-trained networks capable of creating high-resolution classifiers in brightfield and fluorescence, depending on how much training data and time are available for training and optimization.

Curious to see HALO AI in action on your images?

Advanced Phenotyping

Cell phenotyping can be used on any of the myriad supported image types to automatically assign cells into user defined phenotypes. Simply select a nuclear or membrane segmentation network, provide a few quick training examples, and train the network to identify phenotypes of interest.

Phenotyping is a highly effective and flexible tool to quantify cells based on morphology when biomarker information is absent and can assist with quantification and characterization of cells with complex morphologies, such as neuronal cells.

Top Notch Training and Support

At Indica Labs, we take pride in providing top-quality support. Unlimited IT support, scientific support, training, and access to our Learning Portal are included with every license at no additional cost. With support staff in the US, UK, EU, China, and Japan, you are supported in any time zone.

Wondering how easy developing your own algorithm can be without programming experience? Reach out to us to find out how intuitive HALO AI’s train-by-example interface really is.

What Our Customers Have to Say

Read independent reviews on our HALO AI Deep Learning Classifier Add-on and learn how these customers are using Indica Labs’ solutions to streamline their workflows.

Platform Compatibility

HALO AI is compatible with all of the file formats that can be used in HALO and HALO Link. Yours not on the list? Email us your requirements.

File Formats:

Non-proprietary (JPG, TIF, OME.TIFF)
Nikon (ND2)
3DHistech (MRXS)
Akoya (QPTIFF, component TIFF)
Olympus / Evident (VSI)
Hamamatsu (NDPI, NDPIS)
Aperio (SVS, AFI)
Zeiss (CZI)
Leica (SCN, LIF)
Ventana (BIF)
Philips (iSyntax, i2Syntax)
KFBIO (KFB, KFBF)
DICOM (DCM*)
*whole-slide images

Advancing Discovery with AI: Features of HALO AI

Quickly acquire training annotations in either brightfield or fluorescence with the new AI annotation tool in HALO AI. Simply point and click your object of interest to add an annotation.

Use real-time tuning in HALO AI to watch a network as it trains in real time. Toggle the mark up on and off to evaluate performance, choose to add training data, or change parameters on-the-fly.

Once a HALO AI model is trained, a probability map can be used as an alternative output to a traditional mask to evaluate performance. Use real-time tuning to select an appropriate probability cut-off for a given class and view the output in a heatmap where blue represents the lowest probability and red the highest.

Investigate results with interactive markup images where you can toggle on and off each population of interest. Interactive markups can be combined with probability thresholding and are especially valuable in exploring validation outputs.

Deploy your HALO AI models in the context of HALO modules for maximum image analysis utility. Choose to utilize one or more models such as nuclear segmentation, membrane segmentation, tissue classification, cell or object phenotyping, and/or SlideQC.

Collaborate on the development of AI using the HALO Link collaborative image management platform. Simply invite your colleagues to a study and have them add training data.

Create classifier pipelines by connecting multiple classifiers or AI Apps into a single workflow. Choose to run within HALO AI or within a HALO module.

Model interoperability leveraging an open format ONNX allows you to move networks between machines, bring in outside ONNX models, or export your model in the ONNX format thanks to the flexible import and export options in HALO AI.

Leverage the three-part Train – Validate – Test workflow to address the question: How good is my HALO AI classifier? Quantitative metrics are output based on the type of network.

Speed up your HALO AI analysis by adapting your trained network for your specific GPU. Also, you can queue training jobs based on number of iterations or time and set it to run at the end of your workday to maximize productivity and evaluate multiple model variants.

Discover HALO AI Apps

Explore our most popular HALO AI apps. You can filter by category and use the arrows at the bottom of the list to view additional options.

All Breast Cancer Brightfield Cancer Cell Quantification Cell Phenotyper Immunohistochemistry Oncology Tissue Classifier Colorectal Cancer Gastric Cancer Head & Neck Squamous Cell Carcinoma H&E Non-Small Cell Lung Cancer Ovarian Cancer Lymphocyte Quantification Immuno-Oncology

Breast IHC Tumor Tissue Detection

The Breast IHC Tumor Detection App is a pre-trained HALO AI classifier designed to detect, segment, and quantify tumor and other area across hematoxylin and DAB-stained whole-slide digital images of breast cancer.

NSCLC IHC Tumor Tissue Detection

The NSCLC IHC Tumor Detection App is a pre-trained HALO AI classifier designed to detect, segment, and quantify tumor area and non-tumor area across hematoxylin and DAB-stained whole-slide digital images of NSCLC.

NSCLC IHC Cancer Cell Phenotyper

The NSCLC IHC Cancer Cell Phenotyper App is a pre-trained HALO AI object phenotyper designed to detect, segment, and quantify non-cancer cells, IHC-positive cancer cells and IHC-negative cancer cells across hematoxylin and DAB-stained whole-slide digital images of NSCLC.

Breast IHC Cancer Cell Phenotyper

The Breast IHC Cancer Cell Phenotyper App is a pre-trained HALO AI object phenotyper designed to detect, segment, and quantify cancer cells and other cells across hematoxylin and DAB-stained whole-slide digital images of breast cancer.

NSCLC H&E Cancer Cell Phenotyper

The NSCLC H&E Cancer Cell Phenotyper App is a pre-trained object phenotyper designed to detect, quantify, and segment cancer cells from non-cancer cells across H&E-stained whole-slide digital images of NSCLC.

CRC H&E Cancer Cell Phenotyper

The CRC H&E Cancer Cell Phenotyper App is a pre-trained HALO AI object phenotyper designed to detect, segment, and quantify cancer cells and other cells across H&E-stained whole-slide digital images of colorectal cancer.

Pan Cancer H&E Lymphocyte Cell Phenotyper

The Pan-Cancer H&E Lymphocyte Cell Phenotyper App is a pre-trained HALO AI object phenotyper designed to detect and quantify lymphocytes across whole slide H&E-stained images of multiple tumor types.

Gastric H&E Tumor Tissue Detection

The Gastric H&E Tumor Tissue Detection App is a pre-trained HALO AI masking classifier designed to segment tumor, stroma, necrosis/other, and glass areas across H&E-stained whole slide images of gastric cancer.

HNSCC H&E Tumor Tissue Detection

The Head & Neck Squamous Cell Carcinoma (HNSCC) H&E Tumor Tissue Detection App is a pre-trained HALO AI masking classifier designed to segment tumor, stroma, necrosis/other, and glass area across H&E-stained whole slide HNSCC images.

NSCLC H&E Tumor Tissue Detection

The Non-Small Cell Lung Cancer (NSCLC) H&E Tumor Tissue Detection App is a pre-trained HALO AI masking classifier designed to segment tumor, stroma, necrosis/other, and glass area across H&E-stained whole slide images of NSCLC.

Ovarian H&E Tumor Tissue Detection

The Ovarian H&E Tumor Tissue Detection App is a pre-trained HALO AI masking classifier designed to segment tumor, stroma, necrosis/other, and glass area across H&E-stained whole slide images of ovarian cancer.

Free Image Analysis

See HALO AI in action on up to three of your images with a free analysis.

Knowledge Center

Learn more about HALO AI by exploring the tabs below. For an introduction to the capabilities of HALO AI, we recommend you check out our HALO AI white paper!

COMET™ and RNAscope™ Image Analysis Using HALO and HALO AI

Read this collaborative app note to learn how our Pharma Services team leveraged the HALO FISH-IF and Spatial Analysis modules and HALO AI for analysis of COMET™ and RNAscope™ images.

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SlideQC Application Note

Read this app note to learn how our AI-powered SlideQC BF quality control algorithm can help enhance efficiency, improve the quality of diagnostic, research, and archival material, and future-proof labs.

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Characterizing the TME using IMC and HALO® Image Analysis

See in this app note how automated analysis of highly multiplexed IMC images using HALO® and HALO AI yields rich cellular and spatial data from a streamlined workflow.

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Glomeruli Quantification and Characterization Application Note

Don’t let varied stain selections hold back your digital image analysis of kidney sections! With HALO AI you can develop a tissue classifier that accurately detects and segments glomeruli in sections across a range of stains including H&E, trichrome, PAMS, and DAB with hematoxylin.

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RNAscope™ Image Analysis Using HALO and HALO AI

Using our ISH module for brightfield and our FISH module for fluorescence, we demonstrate how to quantify ISH signal from RNAscope® assays on a per cell or per unit area basis and output an overall expression score based on ACD Bio’s recommended scoring guidelines.

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HiPlex RNAscope™ Application Note

Using our FISH module we demonstrate how to perform 12-plex RNAscope image analysis using ACD’s HiPlexv2 assay.

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Identifying Islets with HALO AI

Learn how HALO AI can detect islets of variable morphology in H&E-stained pancreatic tissue

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Camelyon 17 Application Note

CAMELYON17 challenged teams to develop automated methods for identifying and staging breast cancer metastases; read how the performance of a HALO AI classifier stood out among commercial entries!

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HALO Platforms for Life Sciences Brochure

Download our brochure to learn about our HALO, HALO AI, and HALO Link platforms, and how they can advance your digital pathology image analysis and management workflows.

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HALO, HALO AI, & HALO Link Cloud Services Brochure

Discover how our Cloud Services team can provide a secure, scalable, and flexible cloud deployment of HALO, HALO AI, and HALO Link.

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HALO in the Cloud at the University of Washington

Read this case study to learn how partnering with our Cloud Services team has delivered greater scalability and cost efficiency for the BioRepository and Integrated Neuropathology laboratory at University of Washington Medicine.

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NCI Case Study

Download this case study to learn about considerations the National Cancer Institute made when planning to migrate its HALO, HALO AI, and HALO Link deployments to the cloud, and benefits the NCI experienced after migration, including 50% faster HALO image analysis.

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Cloud Services and AI Diagnostics Case Study

Learn how the optimized, scalable infrastructure provided by Indica Labs Cloud Services enables the rapid development and robust collaboration of our AI Diagnostics group, powering the next generation of automated AI-based decision support tools.

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Clustering Workflow eBook

Check out our collaborative eBook with Lunaphore to learn about an optimized workflow for extracting information from hyperplex datasets and illuminating changes in cellular neighborhoods using HALO, HALO AI, and the Lunaphore COMET platform.

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Lunaphore COMET Hyperplex IF and HALO® Image Analysis eBook

Our collaborative eBook with Lunaphore shows how HALO and HALO AI, alongside the Lunaphore COMET instrument, enable a high-throughput workflow for phenotypic and spatial analysis of cells in the tumor microenvironment.

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Sequential Same Slide mIF and H&E eBook

Reveal more data on a single slide with this workflow for sequential same slide multiplex IF and H&E staining and imaging using HALO and HALO AI.

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Qualitative and Quantitative Evaluation of the TME eBook

Check out this ebook to see how AI-based nuclear segmentation and tissue classification can streamline cell phenotyping across tissue compartments and samples.

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Characterizing the TME of a Colorectal Adenocarcinoma Sample with the Orion Spatial Biology Platform and HALO Image Analysis

Download our collaborative poster with RareCyte to learn how to analyze a colorectal adenocarcinoma sample with HALO and HALO AI

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Lunaphore COMET Hyperplex IF and HALO® Image Analysis of the TME

Download our collaborative poster with Lunaphore to see how HALO and HALO AI, alongside the Lunaphore COMET instrument, enable a high throughput workflow for phenotypic and spatial analysis of cells in the tumor microenvironment.

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Clustering Workflow for Advanced Cell Phenotyping of Hyperplex IF Images

Download our collaborative poster with Lunaphore to learn about a clustering workflow that uses unsupervised learning for COMET™ images.

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Spatial Characterization of the TME with Cell DIVE Multiplexed Imaging and HALO Image Analysis

Check out our collaborative poster with Cell Signaling Technology and Leica Microsystems to learn about a combined workflow for spatial analysis of the TME.

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Quantitative Image Analysis of a Combined FISH-IF Assay

Learn how to detect protein and RNA in a single assay using ACD’s Co-Detection workflow and HALO image analysis.

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Characterizing the TME Using IMC and HALO Image Analysis

Download this poster to learn how HALO and HALO AI can be used to analyze imaging mass cytometry data.

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Automated Tumor Budding Quantification in Colorectal Carcinoma H&E Images

Learn about quantification of tumor budding in colorectal carcinoma using HALO and HALO AI.

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Evaluation of the TME by High Resolution 17-plex IF and HALO Image Analysis

Learn how to perform highly multiplexed IF and image analysis using the Orion instrument combined with HALO and HALO AI image analysis.

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Our HALO AI customers are making vital discoveries in oncology, neuroscience, and metabolism research with over 150 publications and growing! Check out some of the research our customers are publishing.

HALO AI Publications and Creative Applications

Check out this publication list to find recent high impact HALO AI publications and highlights of several studies leveraging AI in creative or unusual applications.

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HALO AI High Impact Publications

Review this selection of high-impact publications for examples of HALO AI applications in fields ranging from metabolism to immuno-oncology and myology.

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Mouse fetal growth restriction through parental and fetal immune gene variation and intercellular communications cascade

Fetal growth restriction (FGR) is a significant concern in obstetrics, affecting 5–10% of pregnancies globally. FGR is a major contributor to perinatal morbidity and mortality and poses a significant maternal risk due to potential co-occurrence with pre-eclampsia. Despite their impact,...

Prognostic Value of CD8+ Lymphocytes in Hepatocellular Carcinoma and Perineoplastic Parenchyma Assessed by Interface Density Profiles in Liver Resection Samples

This study examined CD8+ cell distribution in hepatocellular carcinoma (HCC) and peritumoral liver tissue to investigate the overall survival (OS) and recurrence-free survival (RFS). It is well understood that CD8+ lymphocytes are involved in both the anti-tumor response and in...

Polycomb deficiency drives a FOXP2-high aggressive state targetable by epigenetic inhibitors

EZH2 is the catalytic component of Polycomb Repressive Complex 2 (PRC2) and performs trimethylation of histone H3 at lysine 27 (H3K27me3) to silence chromatin. PRC2 is known to play different roles in different cancers and inhibitors of PRC2 histone methyltransferase...

HALO AI White Paper

Check out this white paper for an in-depth introduction to the deep learning-based add-on to HALO, including available networks, common functions, and the “train – validate – test” Validation workflow.

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Pharma Services and HALO Link White Paper

Download our white paper to learn how Indica Labs’ Pharma Services collaborates with customers and delivers HALO and HALO AI image analysis using HALO Link.

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Quantitative RNAscope™ Image Analysis Guide

From experimental design considerations to optimized setup of HALO image analysis parameters, our guide will help take your quantitative RNAscope™ image analysis to the next level.

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Getting Started with Multiplex Fluorescence Image Analysis in HALO®

11 June 2025 | Learn the basics of multiplex fluorescence image analysis!

Getting Started with In Situ Hybridization in HALO®

22 May 2025 | Learn the basics of in situ hybridization image analysis!

Masterclass: High Dimensional Analysis in HALO®

10 April 2025 | Learn about workflows for highly multiplexed image analysis, including in the new HALO High Dimensional Analysis module!

Getting Started with Brightfield Image Analysis in HALO®

3 April 2025 | Join us for an introductory webinar on brightfield image analysis in HALO®, designed for beginners. We’ll walk through key digital pathology

Indica Labs Joins the AWS Partner Network

Albuquerque, NM, December 4, 2024 – Indica Labs, the global leader in AI-powered digital pathology software and services, announced today that they have joined the

The Institute of Molecular Pathology and Immunology of the University of Porto (IPATIMUP) Selects Indica Labs’ HALO AP® to Deliver AI-enabled Diagnostics

Albuquerque, NM, October 30, 2024 – The Institute of Molecular Pathology and Immunology of the University of Porto (IPATIMUP), among the leading institutes for clinical

Indica Labs Announces Suite of HALO AI Apps to Power Life Sciences Image Analysis Workflows

Albuquerque, NM, August 15, 2024 – Indica Labs today announces expansion of AI capabilities for life science with the launch of HALO AI Apps, pre-trained

Indica Labs Expands Availability of HALO Digital Pathology Solutions in Asia Pacific Region Including CE-IVDR Marked HALO AP® Platform

Albuquerque, NM – 2 July 2024 – Indica Labs today announces the expansion of their reseller network in the Asia Pacific (APAC) region.

HALO®, HALO AI, and HALO Link 4.1 Features and Functionalities

In this blog post, you can learn about some of the new features in the 4.1 release including the new High Dimensional Analysis module, when

Open Pathology and AI Integrations: Empowering Labs with Choice

In digital pathology, advancements and proliferation in artificial intelligence (AI) and digital laboratory equipment are enabling streamlined workflows and new insights. However, they can also

Looking Back: Reviewing 2024 at Indica Labs

As 2024 draws to a close, we at Indica Labs would like to thank the customers and collaborators who helped fill 2024 with exciting discoveries,

Classifier Pipelines in HALO AI: Delivering Increased Efficiency for Sequential Classifier Workflows

AI is helping to advance digital pathology research by streamlining workflows, increasing reproducibility, and enabling the collection of previously intractable data.

Indica Labs’ Boston HALO® User Group Meeting

15 May 2025 | Indica Labs is pleased to announce our Boston HALO® User Group Meeting at Le Méridien Boston Cambridge on May 15 from

China User Group Meeting 2024

1 November 2024

Japan User Group Meeting 2024

25 October 2024

Indica Labs’ London HALO® User Group Meeting 2024

10 December 2024 | Indica Labs is pleased to announce our London HALO User Group Meeting to be held in London on 10 December 2024

Deploy HALO® and HALO AI in a Fully Managed Cloud-Hosted Environment

Indica Labs offers optimized deployments of HALO and HALO AI software hosted in Amazon Web Services (AWS). We manage all aspects of implementation and ongoing maintenance to provide a highly performant, scalable, and secure AI-enabled HALO environment in the cloud. You maintain full ownership over your AWS account while our AWS Certified Solutions Architects manage your infrastructure and HALO software environments.

Learn more about benefits of cloud-hosted environments in our recent blog post. Or reach out today to our Cloud Services team by using the form below, to learn whether a managed cloud deployment is right for you.