The Pan-Cancer H&E Lymphocyte Cell Phenotyper App is a pre-trained HALO AI phenotyper optimized to detect and quantify lymphocytes across whole slide H&E-stained images of multiple tumor types. Outputs include total cells and percentage of total cells that fall into each three cell phenotypes, lymphocyte, cancer cell, and other cell. The App can classify cells within regions of interest, fields of view, or across entire images and can be combined with other HALO® image analysis modules and other HALO AI Apps to derive further quantitative outputs and measurements. In the example shown below, the App is combined with the HALO Spatial Analysis Module to analyze the proximity of lymphocytes to cancer cells. As an RUO product, the AI 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?
- The Pan-Cancer H&E Lymphocyte Cell Phenotyper App
Training Information
- The Pan-Cancer H&E Lymphocyte Cell Phenotyper App training was performed using 36,000+ annotations from hundreds of H&E-stained whole slide images of multiple tissues, including Bladder Cancer, HNSCC, CRC, TNBC, Normal Liver, Cervical Cancer, NSCLC, Uterine Cancer, Normal Small Intestine, Normal Breast, Normal Tonsil, Normal Uterus, Normal Prostate, Normal Colon.
- While the Pan-Cancer H&E Lymphocyte Cell Phenotyper separates cancer and stromal/other cell phenotypes from lymphocytes, only the lymphocyte counts were validated. If cancer cell counts are needed, we recommend performing additional training and validation. We also offer Cancer Cell Phenotypers for individual indications which may demonstrate superior performance.
- Tissues were obtained from multiple institutes using different scanner types to improve overall generalizability. 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.
Optimized for 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 trained further with your data. Shown here, the Pan-Cancer H&E Lymphocyte Cell Phenotyper App used out-of-the-box to detect lymphocytes (gold in markup) in H&E tissues of breast cancer, colorectal cancer, and non-small cell lung cancer.
Seamlessly Integrate with Other HALO AI Apps and HALO Image Analysis Modules
The Pan-Cancer H&E Lymphocyte Cell Phenotyper App can be used in conjunction with other HALO AI Apps or HALO modules to derive additional quantitative outputs. In the examples hown here, cancer cells and lymphocytes segmented by the Pan-Cancer H&E Cell Phenotyper are analyzed further using the Proximity Analysis function available with the HALO Spatial Analysis Module. Here, we plot and measure the distance and number of lymphocytes (yellow dots) within 50 microns of cancer cells (blue dots). The distances are are binned to create a histogram as shown in the upper right corner. Closer proximity between cancer cells and lymphocytes and higher density of lymphocytes may infer more interaction between the two cell populations within the tumor microenvironment.
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 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.
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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.
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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.
Learn MoreUse the arrows above to view additional related AI apps
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