Improving cerebral microvascular image quality of optical coherence tomography angiography with deep learning‐based segmentation

Fan, Fan; Zhang, Jisheng; Zhu, Lianqing; Ma, Zongqing; Zhu, Jiang

doi:10.1002/jbio.202100171

Cited by 3 publications

(1 citation statement)

References 16 publications

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“…This oversight often results in a compromised performance in more complex scenarios. Additionally, modern IQA models tend to rely on intricate post-processing steps, which not only increase the computational burden but also raise the barrier to their practical application [21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Innovative Approaches in Image Quality Assessment: A Deep Learning-Enabled Multi-Level and Multi-Scale Perspective

Sun

2023

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In the dynamic field of digital image technology, the imperative role of Image Quality Assessment (IQA) is increasingly recognized. Traditional methodologies, designed to echo human visual processing, frequently encounter challenges in diverse application landscapes, primarily due to their singular focus on limited scale and level analysis. This shortcoming curtails their efficacy in practical scenarios. The incorporation of deep learning paradigms into IQA has notably enhanced evaluation capabilities. Yet, there remains a scope for refinement, especially in areas like integrating multi-scale data, fusing features at multiple levels, and optimizing computational resources. Addressing these gaps, this study proposes an advanced multi-level and multi-scale IQA strategy, harnessing the power of deep learning. A unique end-to-end multi-scale IQA module has been crafted, tailored to aggregate image quality data across a spectrum of scales comprehensively. Additionally, this research introduces an IQA model built upon the foundation of multi-level feature fusion. This innovative model stands out in its capacity to efficiently assess image quality, by adeptly extracting and amalgamating features from various levels. Beyond enhancing accuracy in quality scoring, this approach significantly bolsters the model's interpretability and operational efficiency, marking a stride forward in digital image processing research and applications.

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Section: Introductionmentioning

confidence: 99%

Innovative Approaches in Image Quality Assessment: A Deep Learning-Enabled Multi-Level and Multi-Scale Perspective

Sun

2023

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Handheld optical coherence tomography for tissue imaging: current design and medical applications

Liu,

Meng,

Wang

et al. 2024

Applied Spectroscopy Reviews

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Optical coherence tomography angiography allows longitudinal monitoring of angiogenesis in the critical-sized defect model

Shen,

Bu,

et al. 2023

Front. Phys.

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Purpose: This study aims to evaluate the capability of optical coherence tomography angiography (OCTA) for imaging the microvasculature within a critical bone defect, to longitudinally observe vascular alterations, and quantify the microvascular density and morphology in a model of a critical-sized defect.Methods: An OCTA system was used to longitudinally monitor angiogenesis in four rat models presenting critical-sized defects with observations recorded on days 7, 14, and 28 post-defect creation. Simultaneously, angiogenesis in three additional rat models was evaluated through a conventional histological analysis involving hematoxylin and eosin staining.Results: OCTA was successful in acquiring in vivo 3D vascular perfusion mapping within the critical-sized defect, and it allowed for quantitative analysis of the microvasculature’s density and morphology. The OCTA imagery of the blood microvasculature revealed a noticeable augmentation in the number and size of vessels, with more extensive vessel convergence observed on day 14 compared to both days 7 and 28. Complementing these observations, quantitative analysis demonstrated that the vessel area density (VAD) and maximum vascular diameter index (MVDI) were significantly larger on day 14 in comparison to measurements taken on days 7 and 28.Conclusion: Leveraging its ability to capture high-resolution images, OCTA facilitated longitudinal monitoring of angiogenesis in models of critical-sized defects. Therefore, it potentially serves as a non-invasive experimental tool beneficial for bone regeneration research.

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Improving cerebral microvascular image quality of optical coherence tomography angiography with deep learning‐based segmentation

Cited by 3 publications

References 16 publications

Innovative Approaches in Image Quality Assessment: A Deep Learning-Enabled Multi-Level and Multi-Scale Perspective

Innovative Approaches in Image Quality Assessment: A Deep Learning-Enabled Multi-Level and Multi-Scale Perspective

Handheld optical coherence tomography for tissue imaging: current design and medical applications

Optical coherence tomography angiography allows longitudinal monitoring of angiogenesis in the critical-sized defect model

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