Rapid on-site evaluation (ROSE) Solution for EBUS-TBNA that assists in adequacy assessment, diagnosis, and staging of lung cancer.

	Rapid on-site evaluation (ROSE) for adequacy assessment of EBUS-TBNA aspirates.
	Aids accurate and faster diagnosis and staging of lung cancer.
	Analyses of whole slide images of conventional PAP (Papanicolaou) stained cytology smears.
	Rapid onsite reporting with increased yield eliminating need for repeat procedures.
	Optimised hospital stay and cost benefits to the patient.
	Objective, evidence-based, and precise reports with fewer reviews.
	24/7 reporting with batch analysis.
	Strong agreement of 0.92 (Cohen’s Kappa) with manual adequacy assessment by pathologists.

	Algorithms for identification and segmentation of tumours in Hematoxylin and Eosin (H&E) stained whole slide images.
	Algorithm features include: tumour identification, tumour/stroma segmentation and tumour localization.
	Algorithm outputs validated for use on Non Small Cell Lung Carcinoma (NSCLC), breast carcinoma, pancreatic ductal adenocarcinoma and Head and Neck Squamous Cell Carcinoma (HNSCC).

	Solution for accurate quantification of Estrogen/Progesterone receptor expression in breast carcinoma.
	Aids disease stratification, prognostication and treatment decisions.
	Segmentation and quantification models of tumour nuclei (positive and negative) to compute Allred scores.
	Automated exclusion of in-situ malignancy from quantification.
	Available as both semi-automated and automated workflow solutions.
	Applicable on selected regions of interest (ROI) as well as whole slide images.
	Improves accuracy, reproducibility and throughput of biomarker reporting.
	Very good agreement with pathologists; Sensitivity, Precision, and F1-score of 0.99, 0.84, 0.91 respectively .

	Solution for accurate quantification of Her-2/Neu expression in breast carcinoma.
	Aids disease stratification, prognostication and treatment decisions.
	Segmentation, quantification and grading of membrane positivity and intensity.
	Automated exclusion of in-situ malignancy from quantification.
	Available as both semi-automated and automated workflow solutions.
	Applicable on selected regions of interest (ROI) as well as whole slide images .
	Improves accuracy, reproducibility and throughput of biomarker reporting.
	Strong agreement (0.91 Quadratic Kappa) with pathologists scoring.

	Solution for mitotic index calculation.
	Aids in prognostication, disease stratification and treatment decisions.
	Applicable to Hematoxylin and Eosin based sections from breast carcinoma and Head & Neck Squamous Cell Carcinoma (HNSCC).
	Analyses of “field of view” images as well as whole slide images.
	Provides mitotic figure segmentation, classification, with improved accuracy of mitotic index calculation.
	Strong and significant correlation (r = 0.91, p <.001) with manual assessment methods.

	Solution to aid accurate disease stratification in prostate carcinoma.
	Automated tumour/stroma segmentation.
	Pixel level Gleason grading as well as section level Gleason scoring.
	Applicable on Tissue Micro Arrays (TMA), needle core biopsies, and radical resection specimens.

	PanIN are microscopic epithelial precursor lesions of pancreatic ductal adenocarcinoma (PDAC) that serve as surrogate markers for invasive carcinoma elsewhere in the organ.
	Solution for segmentation of PanIN lesions in Hematoxylin and Eosin (H&E) stained sections of human pancreas.
	Accurate segmentation, grading of PanIN regions and invasive carcinoma in whole slide images of pancreas.
	Sensitivity of 91.56% and Specificity of 85.68% in comparison with manual assessment by pathologists, for detection of PanIN.

	Solution for comprehensive reporting of Radical Prostatectomy specimens.
	Gleason grading and staging with quantification of primary, secondary and tertiary patterns.
	Segmentation and quantification of additional diagnostic, prognostic and predictive parameters to aid disease stratification, prognostication and treatment decisions.
	Synoptic, customizable reporting formats.
	Correlation with multi-modality data, to improve accuracy of reporting.

	PD-L1 protein expression has emerged as a biomarker with capabilities to predict patient response to immunotherapy.
	Algorithm to aid patient selection for treatment with anti PD1/PDL-1 antibodies in lung carcinoma.
	Networks for tumour segmentation, tumour cell detection and classification, with computation of the Tumour Proportion Score (TPS).
	Both semi-automated and automated workflows available.
	Applicable to selected regions of interest (ROI) as well as whole slide images.

	Solutions for retinal disease identification, diagnosis and grading.
	Classification and grading of retinal diseases like Diabetic Retinopathy, Age-related Macular Degeneration, Glaucoma, and others, using colour fundus images.
	Sensitivity for retinal disease classification across classes range between 88% to 99%.