The Non-Small Cell Lung Cancer (NSCLC) H&E Cancer Cell Phenotyper App is a pre-trained HALO AI phenotyper designed to detect and quantify cancer cells across whole slide H&E-stained images of primary and metastatic NSCLC. Outputs include total cells and percentage of total cells that are cancer and non-cancer (other). The App can be used to quantify cancer cells in regions of interest, fields of view, or across entire images and can be combined with HALO® Analysis Modules and other HALO AI Apps to derive further quantitative outputs and measurements, as shown in the example below. 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?
- NSCLC H&E Cancer Cell Phenotyper App
- Nuclear Segmenter App optimized and trained for use with the NSCLC H&E Cell Phenotyper App
- Benign Epithelia Classifier – Used to identify and exclude benign epithelia from analysis. Please note, the NSCLC H&E Cancer Cell Phenotyper App can be used with or without the Benign Epithelia Classifier.
Training Information
- The NSCLC H&E Cancer Cell Phenotyper training was performed using 165,000+ annotations from hundreds of H&E-stained whole slide images of primary NSCLC.
- 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.
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 own data. Shown here, the NSCLC H&E Cancer Cell Phenotyper App used out-of-the-box to detect tumor in H&E tissues with variable morphology and stain intensities.
Seamlessly Integrate with Other HALO AI Apps and HALO Image Analysis Modules
The NSCLC H&E Cancer Cell Phenotyper can be used in conjunction with other HALO AI Apps or HALO modules to derive additional quantitative outputs. In the example shown here, the NSCLC H&E Cancer Cell Phenotyper outputs are used with our HALO Spatial Analysis Module to create a density heatmap of cancer cells across the tissue. In the resulting mark-up image, “hotspots” or areas where cancer cells are more dense are marked in progressively hotter color tones (yellow, orange and red), while blue areas represent areas of the tissue where cancer cells are absent. Density heatmaps of cancer cells can help guide manual macrodissection of tissues and estimate cancer cell content in dissected regions.
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 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.
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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.
Learn MoreUse the arrows above to view additional related AI apps
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