Hessian filter-assisted full diameter at half maximum (FDHM) segmentation and quantification method for optical-resolution photoacoustic microscopy

TL;DR

This paper introduces a Hessian filter-assisted adaptive thresholding algorithm for vessel segmentation in optical-resolution photoacoustic microscopy, improving detection of subtle vascular changes and quantification accuracy over traditional methods.

Contribution

The study presents a novel vessel segmentation method that enhances sensitivity and accuracy in quantifying vascular responses in photoacoustic imaging.

Findings

Detected twice larger vasoconstriction in antihypotensive studies.

Successfully identified 18.8% vasodilation in antihypertensive cases.

Outperformed traditional Hessian filter method in change detection.

Abstract

Optical-resolution photoacoustic microscopy has been validated as a high-resolution and high-sensitivity imaging modality for angiographic studies in the past decades. Quantitative vascular analysis reveals critical information of physiological changes, where vessel segmentation is the key step. In this work, we developed a Hessian filter-assisted, adaptive thresholding vessel segmentation algorithm. Its performance is validated by a digital phantom and in vivo images. Its capability of capturing subtle vessel changes is further tested in two longitudinal studies on vascular responses to blood pressure agents. The results are compared with the widely used Hessian filter method. In the antihypotensive case, the proposed method detected a twice larger vasoconstriction than the Hessian filter method. In the antihypertensive case, the proposed method detected a vasodilation of 18.8 %, while the Hessian filter method failed in change detection. The proposed algorithm could correct errors caused by conventional segmentation methods and improve quantitative accuracy for angiographic applications.