Surreal illustration of OCT scan normalization for diverse eyes.

OCT Scans Getting a Second Opinion: Normalizing Signals for Clearer Results

Nico Varela in Health & Wellness August 2025 • 4 min read.

"Discover how a new signal normalization method is reducing discrepancies between different OCT machines, leading to more reliable eye health measurements."

Optical coherence tomography (OCT) has become a routine part of eye exams, providing detailed images of the retina. With various OCT devices available, each offering different features, comparing measurements between them can be challenging. These discrepancies can hinder consistent monitoring of eye conditions, especially in glaucoma management, where tracking subtle changes over time is crucial.

A recent study tackled this problem by introducing a novel signal normalization method. The goal was to minimize the systematic differences in measurements obtained from different spectral-domain (SD) OCT devices, making the data more comparable and reliable.

The study focused on retinal nerve fiber layer (RNFL) thickness measurements, a key indicator in glaucoma diagnosis and progression. By normalizing the OCT signals, the researchers aimed to create a standardized baseline, allowing for more accurate comparisons regardless of the device used.

Decoding Signal Normalization: Bridging the Gap Between OCT Devices

Surreal illustration of OCT scan normalization for diverse eyes.

The study, involving 109 eyes from 59 participants, used two SD-OCT devices (Cirrus and RTVue) to scan each subject's eyes. The core of the research was to apply a signal normalization technique to the OCT image data, effectively matching the signal characteristics between the two devices. This process involved several steps to compensate for variations in signal strength and quality.

The signal normalization method consisted of:

Z-Scaling and Sampling Density Normalization: Adjusting the axial scale and sampling rate to ensure uniformity across devices.
Amplitude Normalization: Standardizing the pixel dynamic range using histogram-based adjustments.
Signal Strength (SS) Normalization: Compensating for differences in signal quality using a custom high dynamic range (HDR) processing technique.

Following normalization, a custom segmentation software was used to automatically measure the global mean peripapillary RNFL thickness from all images. These measurements were then compared to the original device outputs to assess the effectiveness of the signal normalization method in reducing measurement differences.

The Future of OCT: Standardized Signals for Enhanced Eye Care

The results of the study indicated that signal normalization significantly reduced the systematic differences in RNFL thickness measurements between the two OCT devices. In eyes with thicker RNFL (greater than 62.4 µm), the mean absolute difference was reduced to a mere 2.95 µm, indicating a substantial improvement in measurement agreement.

This normalization method offers a promising approach to enhance the reliability and comparability of OCT measurements across different devices. By minimizing device-specific variations, clinicians can gain greater confidence in tracking disease progression and making informed treatment decisions.

While the study focused on Cirrus and RTVue devices, the researchers suggest that the signal normalization method could be applied to other SD-OCT devices as well. Further studies are needed to validate this approach across a wider range of devices and clinical settings, paving the way for standardized OCT imaging in the future.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: 10.1167/iovs.13-12806, Alternate LINK

Title: Signal Normalization Reduces Systematic Measurement Differences Between Spectral-Domain Optical Coherence Tomography Devices

Subject: General Medicine

Journal: Investigative Opthalmology & Visual Science

Publisher: Association for Research in Vision and Ophthalmology (ARVO)

Authors: Chieh-Li Chen, Hiroshi Ishikawa, Yun Ling, Gadi Wollstein, Richard A. Bilonick, Juan Xu, James G. Fujimoto, Ian A. Sigal, Larry Kagemann, Joel S. Schuman

Published: 2013-11-05

Everything You Need To Know

What is optical coherence tomography (OCT), and why is it used in eye exams?

Optical coherence tomography (OCT) is an imaging technique used during eye exams that provides detailed, high-resolution cross-sectional images of the retina and other eye structures. It uses light waves to capture these images, similar to ultrasound but using light instead of sound. OCT helps in early detection and monitoring of various eye conditions, including glaucoma, macular degeneration, and diabetic retinopathy.

What exactly is signal normalization in the context of OCT scans, and what are its key components?

Signal normalization in OCT scans is a process that adjusts and standardizes the signal characteristics of images obtained from different OCT devices. This ensures that measurements, such as retinal nerve fiber layer (RNFL) thickness, are comparable across devices, minimizing discrepancies caused by variations in signal strength and quality. It typically involves steps like Z-scaling, sampling density normalization, amplitude normalization, and signal strength (SS) normalization.

What are the primary benefits of using signal normalization when comparing OCT scans from different machines?

The main benefit of signal normalization is that it reduces measurement variability between different spectral-domain (SD) OCT machines, leading to more reliable monitoring of eye conditions like glaucoma. When retinal nerve fiber layer (RNFL) thickness is measured, this technique significantly reduces the systematic differences between machines. This is particularly useful when tracking subtle changes over time and across different clinics that might use different OCT devices. The end result is enhanced accuracy and reliability in assessing changes in eye health.

Can you describe the specific methods or techniques used in signal normalization for OCT images?

The study used a novel signal normalization method that consists of three key steps. First, Z-Scaling and Sampling Density Normalization adjust the axial scale and sampling rate to ensure uniformity. Second, Amplitude Normalization standardizes the pixel dynamic range using histogram-based adjustments. Finally, Signal Strength (SS) Normalization compensates for differences in signal quality using a custom high dynamic range (HDR) processing technique. These steps collectively reduce discrepancies in OCT measurements between different devices, enhancing the reliability of results.

What are the broader implications of using signal normalization in OCT imaging for diagnosing and managing eye diseases?

The implications of using signal normalization extend to improved diagnostic accuracy and patient care. By standardizing OCT measurements, clinicians can more confidently monitor disease progression, such as in glaucoma, where subtle changes in retinal nerve fiber layer (RNFL) thickness are critical. This standardization also supports collaborative research and data sharing across different institutions, as measurements become more comparable. Ultimately, it leads to more informed treatment decisions and better outcomes for patients at risk of, or affected by, eye diseases.