Indica Labs – HALO AI

HALO AI

DEEP LEARNING CLASSIFIER

Neural network-driven tissue and cell classification for research and routine pathology.

HALO AI classifiers can be trained to quantify or segment tissue classes, to find rare events or cells within tissues, and to categorize cell populations into specific phenotypes.

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Product Description

Indica Labs - Digital Pathology

The power of artificial intelligence in the hands of the pathologist.

Indica Labs - Digital Pathology

INTUITIVE WORKFLOW

No computer programming or AI knowledge is required.

HALO AI is fully integrated with the intuitive, easy-to-use HALO and HALO Link viewers and employs a simple three-step workflow.

Trained classifiers can be applied to segment tissue and cells on any whole slide image or region of interest.

POWERFUL TISSUE SEGMENTATION

HALO AI includes the option of three powerful neural networks, VGG, DenseNet and MiniNet, a custom network developed at Indica Labs and designed to produce a solution quickly with limited training data.

Available probability markups allow visualization of uncertainty in tissue classification, facilitating network training.

Indica Labs - Digital Pathology
Indica Labs - Digital Pathology

ACCURATE SEGMENTATION OF CELLS AND NUCLEI

Segment nuclei with HALO AI’s nuclei segmentation classifier, with pretrained networks for H&E, single IHC, or DAPI stained images for an out of the box solution.

Quickly train your own nuclei segmentation network for specific applications, like unique tissue or advanced staining protocols.

CLASSIFICATION OF NUCLEI INTO PHENOTYPES

HALO AI includes the Nuclei Phenotyper classifier which is compatible with brightfield and fluorescence images and designed to automatically assign cells into user-defined phenotypes.

Define your phenotypes with a few quick training examples and HALO AI does the rest.

Indica Labs - Digital Pathology

HALO AI TISSUE CLASSIFICATION EXAMPLES

Indica Labs - Digital Pathology

More Solutions from Indica Labs

Additional Information

Clinical | Research Suitability

Research

Imaging Modality Supported

Brightfield, Fluorescence, IMC, MIBI

User Customizable | Application-Specific Algorithms

Application Specific, User customizable

Max No. Multiplexed Biomarkers

>50 Biomarkers, unlimited FL and FISH multiplex

Research Use Only Applications

User Customizable Algorithms Suitable for Multiple Applications

On-Premise Deployment

yes

Cloud Deployment

yes

TMA Support

yes

File Formats Produced | Supported

.png, .svs, 3DHistech .mrxs, Akoya .qptiff, DICOM, Hamamatsu .ndpi, Hamamatsu .ndpis, Huron .svs, Huron .tif, JP2, JPEG/JPG/JPEG 2000, Leica .afi, Leica .lif, Leica .scn, Leica .svs, Leica Aperio .ome-tif, Leica Aperio .svs, Mikroscan .svs, Mikroscan .tif, Motic .svs, Motic .tif, Nikon .nd2, Objective Imaging .svs, Olympus .vsi, OptraSCAN .jp2, Philips .iSyntax, Philips .tiff, Roche .tif, TIFF/TIF, Ventana .bif, Zeiss .czi, KFBIO.kfb, Whole Slide Images (WSI)

Additional Notes*

HALO AI is a collection of train-by-example classification and segmentation tools., Users can apply pre-trained algorithms or train their own to quantify and segment tissue classes, find rare events and categorize cell populations.

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Application Note

Application Note



HALO AI White Paper

HALO AI White Paper



High Impact Publications

High Impact Publications



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