Abyss Processing Reflectivity
by Abyss Processing
· Based in Singapore →
— 3D AI Solutions for Glaucoma
Paid
Overview
Abyss Processing Reflectivity is an AI-powered software designed to assist in the diagnosis and prognosis of glaucoma by analyzing 3D Optical Coherence Tomography (OCT) images of the optic nerve head (ONH).
- What it does: Reflectivity uses advanced neural networks to restore visibility in OCT images by removing noise, shadows, and artifacts. It performs 3D structural analysis, including “digital staining” to classify and quantify neural and connective tissues of the ONH, and provides a glaucoma risk score. The software aims to offer a more accurate glaucoma diagnosis/prognosis compared to traditional gold-standard parameters.
- Who it is for: This tool is intended for ophthalmologists and other clinicians involved in glaucoma management. It is particularly relevant for specialties and care settings that utilize OCT imaging for eye examinations.
- How it fits a clinical or practice workflow: Reflectivity integrates with Heidelberg Engineering’s HEYEX2 platform. Users can initiate analysis by dragging OCT volumes to the Reflectivity icon within HEYEX2. After cloud-based processing, a comprehensive patient report is generated, including the glaucoma risk score, vital metrics, and details on AI-based segmentation quality. The software is designed to be OCT device agnostic.
- Notable capabilities: Key features include 3D image restoration, 3D structural analysis with digital staining of ONH tissues, and an improved glaucoma diagnosis/prognosis score. It also offers a simplified patient report and OCT denoising. Reflectivity provides structural parameters for both neural and connective tissue within the ONH, including lamina cribrosa parameters, by enhancing deep tissue visibility in OCT scans.
As of the current information, Reflectivity is exclusively designed for research use and is not approved as a medical device for diagnostic purposes.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- 3D AI for Glaucoma Diagnosis & Prognosis
- 3D Image Restoration (noise, shadows, artifact removal)
- 3D Structural Analysis (digital staining of neural and connective tissues)
- OCT Digital Staining & 3D Structural Analysis
- Advanced Neural Networks (Artificial Intelligence)
- Improved and Fast Glaucoma Diagnosis/Prognosis
- OCT Compensation for restoring visibility of glaucoma site
- Simple and Interactive Patient Report
- OCT Denoising
- OCT Device Agnostic
Use Cases
- Streamlining glaucoma diagnosis and prognosis
- Enhancing deep tissue visibility in OCT scans
- Providing comprehensive structural analysis of the optic nerve head in 3D
- Generating precise glaucoma risk scores from OCT scans
- Classifying and quantifying neural and connective tissues of the optic nerve head
- Predicting visual field loss from optic disc drusen
What Physicians Need to Know
Retinal Image Analysis (Fundus/OCT)
Reflectivity primarily focuses on Optical Coherence Tomography (OCT) scans of the optic nerve head (ONH) for 3D structural analysis. It enhances deep tissue visibility in OCT scans by removing noise, shadows, and artifacts, and can classify neural and connective tissues in 3D OCT images.
Glaucoma Detection
The tool provides a precise glaucoma risk score and comprehensive structural analysis of the optic nerve head in 3D from a single OCT scan. It offers advanced features for glaucoma diagnosis and prognosis, including digital staining and 3D structural analysis to classify and quantify neural and connective tissues of the ONH. Studies suggest that Reflectivity's AI algorithms can provide glaucoma diagnosis/prognosis more accurately than other gold-standard glaucoma parameters. The diagnostic performance of ONH scans with AI, achieving an AUC of 0.93 u00b1 0.06, was found to be better than macula scans for glaucoma classification.
Autonomous vs Assistive Diagnosis
Reflectivity is designed as a companion software tool for clinicians. It processes OCT scans via cloud-based services and provides a comprehensive patient report, including a glaucoma risk score and vital metrics, along with information on the quality of AI-based segmentation, to assist healthcare professionals in patient care and assessment. It is currently intended for research use only and is not approved as a medical device for diagnostic purposes.
Point-of-Care Deployment
While the tool integrates with HEYEX2 software, its cloud-based processing suggests a flexible deployment model. However, specific details about point-of-care deployment are not explicitly provided, given its current research-use-only status. Generally, AI in point-of-care diagnostics aims for portability, affordability, and user-friendly interfaces for less experienced personnel.
Screening Program Integration
Reflectivity seamlessly integrates into HEYEX2 through the Heidelberg Appway interface, allowing users to initiate analysis by dragging OCT volumes to the Reflectivity icon. This integration streamlines the process of submitting OCT scans for processing and receiving patient reports. The service is designed to work in conjunction with HEYEX2 software for data submission and retrieval.
Sensitivity & Specificity Data
For glaucoma detection, AI models exploiting 3D structural information of the ONH have shown strong performance. One study using a geometric deep learning model achieved AUCs of 0.77 to 0.88 across visual field defect classifications, with a structure-only model reaching an AUC of 0.83 u00b1 0.02 for superior arcuate defects, improving to 0.87 u00b1 0.02 with the addition of strain information. Another study on glaucoma suspect classification showed AI outperforming residents with 88.6% accuracy, 63.0% sensitivity, and 94.5% specificity. A hybrid deep learning model with reflectance achieved 0.909 sensitivity at 99% specificity and 0.926 at 95% specificity for perimetric glaucoma, with an overall accuracy of 0.948.
Physician Tip
Reflectivity offers a powerful AI-driven 3D structural analysis of the optic nerve head from OCT scans, providing a precise glaucoma risk score and detailed structural parameters, including lamina cribrosa. This can significantly enhance your understanding of glaucoma progression and aid in patient management. The enhanced deep tissue visibility and digital staining capabilities can help in classifying neural and connective tissues, offering insights potentially unmatched by other providers. Remember that currently, Reflectivity is for research use only and not for diagnostic purposes. Always correlate the comprehensive patient reports with your clinical findings and other diagnostic tests for a holistic patient assessment.
Reflectivity is seamlessly integrated into Heidelberg Engineering's HEYEX2 software through the Heidelberg Appway interface. This allows for easy submission of OCT scans (raster or radial volumes) by dragging them to the Reflectivity icon within HEYEX2. The processing is cloud-based, and comprehensive patient reports are returned to the client. This integration streamlines the workflow for optic nerve head analysis within an existing ophthalmology imaging ecosystem.
Details
| Category | Ophthalmology AI |
| Pricing | Paid — 1 token = US$1 = 1 glaucoma report; unlimited monthly or yearly licenses available. |
| Deployment | Cloud-based |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
Unknown AI-estimated Reflectivity is not currently approved as a medical device and is not intended for diagnostic purposes. It is exclusively designed for research use and should be employed solely for research activities that have obtained the necessary ethics approval or Institutional Review Board (IRB) clearance. |
| Integrations | |
| EHR | Not specified |
| Specialties | Ophthalmology |
Ratings & Reviews
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Press & Coverage
Heidelberg Engineering
AI Analytics - Heidelberg AppWay
Abyss Processing's Reflectivity, now available through Heidelberg AppWay, offers advanced AI-powered optic nerve head analysis from a single OCT scan, providing detailed 3D analysis, lamina cribrosa parameters, and a precise glaucoma risk score. The report also includes information on the quality of AI-based segmentation for valuable insights in patient care and assessment.
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Abyss Processing
Reflectivity for HEYEX2 - Abyss Processing
Reflectivity is now integrated into HEYEX2 via the Heidelberg Appway interface, providing comprehensive AI-powered structural analysis of the optic nerve head in 3D and a precise glaucoma risk score from a single OCT scan. It offers a rich array of structural parameters, including critical lamina cribrosa parameters, by enhancing deep tissue visibility in OCT scans.
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Videos
Product demos, reviews, and walkthroughs for Abyss Processing Reflectivity.
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Frequently Asked Questions
Abyss Processing Reflectivity (APR) is a novel AI technique designed to enhance image analysis by accounting for and correcting distortions caused by light reflection and scattering within biological tissues. In ophthalmology, this means more accurate and reliable interpretation of retinal scans, OCT images, and other diagnostic outputs, leading to improved disease detection and monitoring.
APR specifically addresses the challenge of 'noise' introduced by light reflectivity, which can obscure subtle pathological features in ophthalmic images. By providing a clearer, more precise representation of tissue structures, APR-powered AI can detect early signs of conditions like glaucoma, macular degeneration, and diabetic retinopathy with greater sensitivity and specificity than existing AI models that may be more susceptible to these reflective artifacts.
As with any new medical technology, integrating APR will require adherence to relevant regulatory guidelines, such as FDA clearance in the United States or CE marking in Europe, depending on the specific AI product. Physicians should ensure that any APR-enabled AI solution they adopt has undergone rigorous validation and received the necessary approvals for clinical use, and that data privacy regulations like HIPAA are strictly followed.
While APR offers a unique approach to handling reflectivity, other methods exist for improving ophthalmic image analysis, including advanced denoising algorithms, deep learning architectures trained on larger and more diverse datasets, and multi-modal image fusion techniques. Each approach has its strengths and weaknesses, and the optimal solution often depends on the specific clinical application and the type of imaging data being analyzed.
Potential limitations of APR could include its computational demands, requiring specialized hardware or cloud-based processing, and the need for robust validation across diverse patient populations and imaging devices to ensure generalizability. There may also be a learning curve for clinicians to fully understand and trust the outputs of APR-enhanced AI, and the technology's effectiveness might vary depending on the specific type and severity of ophthalmic pathology.
The pricing model for Abyss Processing Reflectivity will likely vary depending on the vendor and the specific AI platform it's integrated into. It could be offered as a subscription service, a per-use fee, or bundled with other AI functionalities. Practices should consider the total cost of ownership, including initial investment, ongoing maintenance, and potential impact on workflow and diagnostic efficiency, when evaluating its financial implications.
Ideally, Abyss Processing Reflectivity would be integrated into AI platforms that are designed to be compatible with standard ophthalmic imaging equipment (e.g., OCT machines, fundus cameras) through established data transfer protocols like DICOM. Seamless integration with EHRs would allow for automated data input and output, streamlining workflows and ensuring that AI-generated insights are readily accessible within the patient's medical record.
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| Last Verified: 2026-07-26 | First Added: 2026-07-26