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Clinical Impact of Using Real-Time Image-Processing Algorithms (Comb Removal and Image Sharpening) in

Kuniharu Tasaki¹, Sujin Hoshi¹, Takahiro Hiraoka¹

¹Department of Ophthalmology, Institute of Medicine, University of Tsukuba, Ibaraki 305-8575, Japan.

Journal of Clinical Medicine

|March 14, 2026

Summary

Novel image processing algorithms for dacryoendoscopy improved procedural efficiency. Image sharpening reduced irrigation fluid use in lacrimal passage intubation, though clinical outcomes showed non-significant favorable trends.

Keywords:

comb-removal algorithm dacryoendoscopy image-processing algorithm image-sharpening algorithm lacrimal duct obstruction

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Area of Science:

Ophthalmology
Medical Imaging
Surgical Technology

Background:

Lacrimal passage intubation is a standard treatment for lacrimal duct obstruction.
Conventional dacryoendoscopes suffer from low resolution and artifacts, hindering visualization.
New image processing algorithms aim to improve dacryoendoscopic visualization.

Purpose of the Study:

To evaluate the clinical impact of comb removal and image sharpening algorithms in dacryoendoscopic surgery.
To assess the effect of these algorithms on procedural efficiency and patient outcomes.

Main Methods:

Retrospective study of 121 sides in 84 patients undergoing lacrimal passage intubation.
Patients categorized into comb-removal and image-sharpening algorithm groups.
Comparison of pain scores, endoscopy duration, irrigation fluid volume, and flow rate; recurrence rates analyzed.

Main Results:

Image sharpening significantly reduced irrigation fluid usage (p=0.012).
Trends towards reduced pain scores and endoscopy duration were observed with image sharpening but were not statistically significant.
The comb-removal algorithm showed no significant impact on evaluated outcomes; recurrence rates were similar between groups.

Conclusions:

Real-time image sharpening enhanced procedural efficiency in dacryoendoscopic surgery.
Favorable trends in clinical outcomes were noted but did not reach statistical significance.
Further research is needed to determine the clinical significance of these image processing algorithms.