AI-Powered Pathology Platform Advances Diagnosis of Prostate, Breast and Gastric Cancer
By LabMedica International staff writers Posted on 06 Sep 2022 |
A transformative cancer diagnostics platform now offers new detection capabilities and a broad feature set to support pathologists and providers with AI-insights that help improve the quality and accuracy of diagnosis, reduce turnaround times and boost productivity.
Ibex Medical Analytics (Tel Aviv, Israel) has launched and rolled out Galen 3.0, a transformative solution offering new detection capabilities and a broad set of features to support pathologists in the diagnosis of multiple tissue types across various digital pathology workflows. Creating a new modality for cancer diagnosis, Galen is the first and most widely deployed AI technology in pathology and used in routine clinical practice at laboratories, hospitals, and health systems worldwide. Galen supports pathologists across numerous diagnostic tasks during the review of breast, prostate, and gastric biopsies and helps improve the quality of cancer diagnosis, reduce turnaround time, boost productivity and improve user experience for pathologists. Galen has demonstrated outstanding outcomes across clinical studies performed in multiple pathology labs and diagnostic workflows
Galen 3.0 incorporates the very latest evolution of Ibex’s AI algorithms for detecting cancer and other clinically relevant features in prostate, breast, and gastric biopsies. To ensure very high accuracy and generalizability, Ibex has trained the deep learning networks on huge, enriched data sets from laboratories worldwide that were digitized by multiple scanning systems, including rare prostatic malignancies such as intraductal carcinoma, neuroendocrine tumor, colorectal adenocarcinoma, lymphoma, and urothelial carcinoma. Galen also calculates a Gleason score, tumor size and percentage for each cancer slide, potentially enabling pathologists to save review time and reduce subjectivity.
Galen 3.0 features an open API (Application Programming Interface) accelerating interoperability and seamless integration with image management solutions, lab information systems and digital pathology workflow solutions. The Ibex API is already used in multiple collaborations between Ibex and leading digital pathology partners where Ibex’s AI findings are seamlessly integrated to the partners’ solutions. Version 3.0 also includes new customizable reporting modules, enabling every customer site to tailor the slide and case reports according to their own needs. Galen 3.0 is CE-Marked, approved in additional countries and now generally available to Ibex customers.
“With an estimated 1.9 million new cancer cases diagnosed in the United States alone this year, we are excited to bring Galen 3.0 to pathology labs worldwide, providing clinically validated, automated decision-support tools that help pathologists diagnose cancer more rapidly and more accurately to support the high demand,” said Issar Yazbin, Vice President of Product Management at Ibex. “Keeping our customers’ needs central to our research and development, we are proud to deploy Galen 3.0, bringing enhanced detection capabilities, improved user experience, increased interoperability tools and ease of implementation into existing clinical workflows.”
Related Links:
Ibex Medical Analytics
Latest Pathology News
- Use of DICOM Images for Pathology Diagnostics Marks Significant Step towards Standardization
- First of Its Kind Universal Tool to Revolutionize Sample Collection for Diagnostic Tests
- AI-Powered Digital Imaging System to Revolutionize Cancer Diagnosis
- New Mycobacterium Tuberculosis Panel to Support Real-Time Surveillance and Combat Antimicrobial Resistance
- New Method Offers Sustainable Approach to Universal Metabolic Cancer Diagnosis
- Spatial Tissue Analysis Identifies Patterns Associated With Ovarian Cancer Relapse
- Unique Hand-Warming Technology Supports High-Quality Fingertip Blood Sample Collection
- Image-Based AI Shows Promise for Parasite Detection in Digitized Stool Samples
- Deep Learning Powered AI Algorithms Improve Skin Cancer Diagnostic Accuracy
- Microfluidic Device for Cancer Detection Precisely Separates Tumor Entities
- Virtual Skin Biopsy Determines Presence of Cancerous Cells
- AI Detects Viable Tumor Cells for Accurate Bone Cancer Prognoses Post Chemotherapy
- First Ever Technique Identifies Single Cancer Cells in Blood for Targeted Treatments
- Innovative Blood Collection Device Overcomes Common Obstacles Related to Phlebotomy
- Intra-Operative POC Device Distinguishes Between Benign and Malignant Ovarian Cysts within 15 Minutes
- Simple Skin Biopsy Test Detects Parkinson’s and Related Neurodegenerative Diseases