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Multimodal Volumetric Retinal Imaging by Oblique Scanning Laser Ophthalmoscopy oSLO and Optical Coherence Tomography OCT

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Pointmaps to Practice: 3D Multi-view Ocular Lesion Mapping.

Vasileios Alevizos^1,2, George A Papakostas³

¹Department of Learning, Informatics, Management and Ethics, Karolinska Institutet, 171 77, Stockholm, Sweden. vasileios.alevizos@pm.me.

Journal of Imaging Informatics in Medicine

|October 24, 2025

Summary

This summary is machine-generated.

This study introduces a novel method for 3D ocular imaging, enabling precise volumetric mapping of uveal melanoma. The technique uses DUSt3R and Logarithmic Positional Partition Interval Encoding (LPPIE) for accurate and memory-efficient 3D reconstruction.

Keywords:

3D reconstruction Depth estimation Multi-view alignment Ocular tumor imaging Volumetric transformation

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Area of Science:

Ophthalmology and Medical Imaging
Computer Vision and Graphics

Background:

Accurate 3D volumetric mapping is crucial for guiding uveal melanoma therapy, as 2D imaging lacks the necessary topological detail for precise boundary delineation.
Existing methods may struggle with the complex geometries and optical properties of the eye, necessitating advanced reconstruction techniques.

Purpose of the Study:

To develop and evaluate a novel pipeline for accurate, memory-efficient 3D ocular volumetry using single-camera input.
To enable precise boundary delineation and volumetric mapping of ocular pathologies, including uveal melanoma.

Main Methods:

Employed DUSt3R for correspondence estimation with self-calibrated poses and dense pointmaps, refined via intrinsic reprojection loss.
Utilized Logarithmic Positional Partition Interval Encoding (LPPIE) for depth data, pointmaps, and camera parameters to minimize memory usage.
Evaluated the pipeline on various ocular images (melanoma, nevus, melanosis, pterygium, phantoms) using metrics like completeness, MAE, RMSE, and rotational/translational errors.

Main Results:

Achieved completeness (C) of approximately 0.43 for melanoma cases, with rotation mismatch around 2°, RMSE of 0.021, and translation error of 3.9 cm.
Simpler morphologies yielded higher completeness (up to 0.61) with stable MAE (0.005-0.008) and high accuracy (δ<1.25 ≈ 0.98-0.99).
LPPIE significantly reduced memory footprint with minimal texture degradation; coherent meshes were generated under modest computational load.

Conclusions:

The proposed method offers a viable approach for accessible ocular volumetry using portable hardware and minimal calibration.
The pipeline demonstrates potential for clinical application in guiding uveal melanoma therapy through accurate 3D reconstruction.
Further refinements could enhance robustness for irregular surfaces, specular reflections, and motion artifacts, improving clinical utility.