1. Suite of solutions to expedite reporting of preclinical toxicologic pathology studies in rodents.

	Set of algorithms to separate and triage sections from different tissues in toxicology studies.
	Pre-sorted images for triaged reporting.
	Automated organ separation to identify organs and enable batch processing.
	Batch analysis for faster turnaround of high throughput toxicology studies.
	Segmentation and quantification of “Not normal” features.
	Quantitative results with comprehensive display of annotated outputs.
	Compliance with INHAND terminology.
	Accelerated translation and application to additional species or tissue types.
	Efficient workflow resulting in significant reduction in drug discovery time.

	Quantification of histomorphological parameters in efficacy models for Chronic Kidney Disease .
	Segments glomeruli and quantifies glomerulosclerosis in Masson Trichrome stained sections from rodent kidney .
	Reduces the time and effort expended in manual annotation of glomeruli and quantification of glomerulosclerosis .
	Improves accuracy and reproducibility of quantification results .

	Solutions for sensitive and consistent detection and quantification of Progressive Cardiomyopathy (PCM) features in rodent heart sections .
	Objective quantification of the histomorphological features of PCM, to assist pathologists in discerning cardiotoxicity-associated changes .
	Accurate severity scoring to help differentiate spontaneous from test article-related findings .
	High values for accuracy, intersection over union, and dice coefficient for each individual feature .
	Strong positive correlation with the median severity grade assigned by panel of pathologists and the percentage area of the heart predicted to have PCM lesions by the algorithm .

	Quantification of histomorphological parameters in NAFLD rodent models .
	Accurate detection and quantification of fatty vacuoles in H&E stained rodent liver sections .
	Differentiation of fatty vacuoles from lumina of blood vessels and bile ducts .
	Strong and significant correlation (r = 0.87, p < .001) with semi-quantitative/manual assessment methods .

	Deep learning and Image processing network to quantify morphological changes in animal models for Bleomycin induced lung fibrosis .
	Accurate and objective segmentation and quantification of histomorphological parameters in rodent lung sections stained with Picrosirius Red and Haematoxyin & Eosin (H&E) .
	High throughput method for quantification of fibrosis in whole slide images of rodent lung.
	No restriction on field of analysis, negating selection bias to improve accuracy.
	Segmentation accuracy of more than 95% across parameters with strong correlation with manual grading using modified Ashcroft’s score.

	Accurate quantification of liver fibrosis to aid evaluation of efficacy models for novel therapies.
	Segmentation and quantification of fibrous septa in Picrosirius stained sections of rodent liver.
	Applicable on microscope based analysis of field of view images as well as whole slide images.
	Strong positive correlation (p < .001) with semi-quantitative assessment by pathologists (Ishak score).

	Automated method to identify the stages of rat spermatogenic cycle in digital images of Hematoxylin and Eosin stained testes.
	Negates the need for assessment of conventional PAS stained sections.
	Aids “stage-aware” histopathological evaluation of testes to detect effects on spermatogenesis in pre-clinical toxicology studies.
	Uses multiple criteria, based largely on the shape and movement of the elongating spermatids within the seminiferous tubule.
	Identifies spermatogenic stage of each tubule, allowing the pathologist to quickly evaluate the testis in a stage aware manner with rapid calculation of the stage frequencies.
	WSI staged in minutes as opposed to several days for manual staging; with objective, quantitative and reproducible outputs.
	Very good agreement for all the stages with Precision, Recall, and F1-score of 0.93 and 0.96 and 0.94 respectively, and overall accuracy of the staging analysis of 0.98.

	Deep Learning and Image Processing solution for automated Estrous staging in rodents.
	Algorithms for evaluation of rodent vaginal and uterine sections, to aid stage aware assessment of female reproductive tissues.
	Segments and quantifies different histological layers, cellular changes and inflammatory cells.
	Sensitivity and Specificity range from 88% to 97% across stages (vaginal sections).