The Breast IHC Cancer Cell Phenotyper App is a pre-trained HALO AI phenotyper designed to phenotype breast cancer cells and normal cells across whole slide images of DAB- and hematoxylin-stained breast cancer tissue. Outputs include total cell count, other cell count, cancer cell count, and the percentages of each. The App can classify tissues within regions of interest, fields of view, or across entire images and can be combined with HALO® Analysis Modules and other HALO AI Apps and to derive further quantitative outputs and measurements. In the example shown below, the App is added to the HALO® Multiplex IHC Module to facilitate analysis of biomarker expression in cancer cells only. As an RUO product, the App can be further trained, tuned, and improved by end users using their own images and data.
Intended Use
For Research Use Only and not intended for clinical diagnostic use.
What's Included?
- Breast IHC Cancer Cell Phenotyper App
- Nuclear Segmenter App optimized and trained for use with the Breast IHC Cancer Cell Phenotyper App
Training Information
- The Breast IHC Cancer Cell Phenotyper training was performed using 103,000+ annotations from hundreds of DAB and hematoxylin-stained whole slide images of breast cancer biopsies and resections.
- Tissues used for training and validation were probed with multiple nuclear and membrane IHC biomarkers and the final training annotation set included both biomarker-positive and negative samples.
- Tissues were obtained from multiple institutes using different scanner types to improve overall generalizability of cancer cell detection. Note, not all of the file formats shown under ‘File Format Compatibility’ tab were included in the training set.
Prerequisites
All pre-trained HALO AI Apps require an existing license of HALO and HALO AI upgraded to version 4.0.5.
File formats supported by the HALO image analysis platform:
- Non-proprietary (JPG, TIF, OME.TIFF)
- Nikon (ND2)
- 3D Histech (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
Accelerate your AI Development
AI is a powerful tool in your image analysis toolbox, but AI development is time consuming and data intensive. Pre-trained using hundreds of images and training annotations, HALO AI Apps give users a jumpstart to accelerate AI development.
Refine with your Training Data
For most applications, HALO AI Apps will work right out-of-the-box, but we realize that it is impossible to test every application. Importantly, HALO AI Apps are ‘open’ and can be further trained by users to optimize and refine performance for specific applications and stains.
Complement your Expertise
HALO AI Apps are designed to handle time-consuming and tedious tasks and providing consistent, standardized measurements. You are free to apply your scientific expertise where it’s needed most – in the interpretation of data to make informed decisions.
Generalizability and Flexibility
Having been trained and tested on tissues with variable staining from different scanners and with multi-institutional data, our HALO AI Apps are designed to achieve the highest level of generalizability right out-of-the-box, but with the flexibility to be further trained with your own data. Here we see the Breast IHC Cancer Cell Phenotyper App used out-of-the-box to detect cancer cells in tissues without DAB staining, as well as tissues with moderate and strong DAB staining in different cellular compartments.
Seamlessly Integrate with Other HALO AI Apps and HALO Image Analysis Modules
The Breast IHC Cancer Cell Phenotyper App can be used in conjunction with other HALO AI Apps or HALO modules to derive additional quantitative outputs. In the example shown here, the Breast IHC Cancer Cell Phenotyper App is added to the HALO Multiplex IHC Module to measure biomarker intensity specifically in cancer cell nuclei (top row) and membranes (bottom row). The cell phenotype mark-up is in the middle column and in the third column, the HALO Multiplex IHC Module is used to assign a 0 to +3 intensity score to cancer cells specifically.
Please note: HALO AI Apps and associated applications are intended for research use only. Please visit our Clinical Products page to discover clinical AI products deployable through our HALO AP® platform.
Free Proof-of-Concept Analysis
See HALO AI Apps in action on up to three of your images with a free proof-of-concept analysis.
Related HALO AI Apps
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.
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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.
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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.
Learn MoreUse the arrows above to view additional related AI apps
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