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Prostate Cancer Biomarker Analysis- OptraSCAN

OptraSCAN offers artificial intelligence & machine learning-based System for accurate, rapid, and reproducible analysis of Prostate Cancer. Contact us at- info@optrascan.com Visit- https://www.optrascan.com/products/optrascan-digital-pathology-scanners

OptraSCAN offers artificial intelligence & machine learning-based System for accurate, rapid, and reproducible analysis of Prostate Cancer.
Contact us at- info@optrascan.com
Visit- https://www.optrascan.com/products/optrascan-digital-pathology-scanners

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®

On-Demand Digital Pathology

Affordable, Subscription-based System

®

OptraScan

Artificial Intelligence & Machine Learning based System for accurate,

rapid and reproducible analysis of Prostate Cancer

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Examination of histological specimens under the microscope by

a pathologist is one of the most reliable methods used in

detection of prostate cancer. This is carried out by examining the

glandular architecture of the specimen by the most common

method for histological grading of prostate tissue - the Gleason

Grading System.

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The cancer tissue is classified from 1 to 5 grades; however, in the

recent times, this common method is found to be ineffective,

reason being:

Ø Analysis on visual interpretation lacks reproducibility

Ø It is limited by intra- and inter-pathologist variability

Our Machine-based scoring algorithms

Our solutions to resolve the challenges appearing

from Gleason Grading :

Ø Fully automated solution : End to end solution

with robust and efficient algorithm modules.

m Intelligent Segmentation module that works

on human perceptible color spaces to detect

cell nuclei based on recognizable patterns like

area, shape, intensity etc.

m Automatic detection of glandular lumens

based on the clustering of identified cell

nuclei and other features.

m Robust feature extraction module to extract

structural, morphometric, texture, nucleocytoplasmic

ratio and color features for

detected cell nuclei and identified glandular

regions.

Gleason score 3+3=6. Grade 1

Gland Formation: Discrete, well formed, uniform large glands arranged back to back

Legend: Lumen Epithelial nuclei Epithelial cell cytoplasm

Gleason score 4+4=8. Grade 4

Gland Formation: Fused, cribriform, poorly formed glands, punched out lumens

Legend: Lumen Epithelial nuclei Epithelial cell cytoplasm

Ø ANN (artificial neural network) based classifier :

m Feature fusion and feature ranking

techniques for representation to the Neural

network based classifier.

m The classifier is trained to distinguish

between moderately and poorly differentiated

glands.

m Object level tumor grading is done using

feature characteristics for malignant and

benign cell nuclei like mean intensity, area,

standard deviation of intensity etc.

Result: Gleason Score 5+5=10. Grade 5

Gland Formation: lacks gland formation, Solid sheet of uniform neoplastic cells

Legend: Epithelial nuclei

Ø Key Differentiator :

m Easily retrainable machine learning system.

m High classification accuracy.


®

OptraScan

®

On-Demand Digital Pathology Solutions

OS-15

15-slide brightfield

OS-120

120-slide brightfield

OS-FS

7-slide frozen sections,

with live view mode

OS-FL

15-slide fluorescence,

with 6 filter cubes

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IMAGEPath

Web-based Image Management and Viewing

TM

TELEPath

Web and Mobile Digital Conferencing

TM

OptraASSAYS

On-Demand Image Analysis

®

CLOUDPath

Laboratory Information Management System

OptraSCAN is an ISO13485 certified company

100 Century Center Court,

Suite 410, San Jose, CA 95112

*All OptraSCAN systems and solutions are for research use only

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