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Deep Learning

At OracleBio, we leverage deep learning technology to enhance our quantitative digital pathology services. We have deep learning modules for both Visiopharm & Indica Labs HALO software platforms. Our team are skilled in the development and application of deep learning algorithms for the quantification of single and multiplex IHC, IF and ISH marker staining in tissue

Examples of how we have recently used Deep Learning to enhance our workflow:

Tumour Identification with Deep Learning OverlayTumour Identification with Deep Learning Overlay

Tumour Identification

In the absence of a PanCK stain, deep learning can enable the identification of tumour region of interest (ROI)

Deep Learning Tumour Heterogeneity Classifier OverlayDeep Learning Tumour Heterogeneity Classifier Overlay

Tumour Staining Heterogeneity

A deep learning approach can significantly reduce the time taken to classify tumour ROI across PDX models containing extensive tumour biomarker staining heterogeneity

idney Glomeruli Deep Learning Detection Analysis Overlayidney Glomeruli Deep Learning Detection Analysis Overlay

Detection of Kidney Glomeruli

Deep learning can support detection of kidney glomeruli across histology special stains for safety/toxicity pathology endpoints

Benefits of OracleBio's Deep Learning Services:

  • Faster Data Delivery – Deep learning can expedite digital pathology workflows, for example by reducing the amount of time required for manual annotations.
  • Improved Accuracy & Reproducibility Deep learning algorithms continually improve and get more precise with every additional training iteration 

  • Complex Analysis – Deep learning supports us in addressing more challenging digital pathology studies

Find out more about our state of the art software capabilities

Deep Learning Classification for Tumour Identification

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