New Frontiers in Retinal Imaging

Hu, Zizhong; Liu, Qinghuai; Paulus, Yannis M.

doi:10.17554/j.issn.2409-5680.2016.02.48

Cited by 10 publications

(7 citation statements)

References 76 publications

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“…In addition, spectroscopic PA imaging is performed to determine the concentration of chromophore, or to quantify the suitable excited wavelength for distinguishing between normal and abnormal tissues [20,26]. Photoacoustic imaging is classified into three groups: photoacoustic tomography (PAT), photoacoustic microscopy (PAM), and photoacoustic endoscopy (PAE) (Figure 2) [15,16], [25,27,28]. PAT typically uses either a single or an array ultrasound transducer to detect the PA signal and target both microscopic and macroscopic imaging, whereas PAM and PAE usually use a focused ultrasound transducer to acquire PA signals and generally image tissue with micron-scale spatial resolution and millimeter-scale depth.…”

Section: Physical Principle Of Photoacoustic Imagingmentioning

confidence: 99%

Photoacoustic Ophthalmoscopy: Principle, Application, and Future Directions

Nguyen

Paulus

2018

J. Imaging

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Photoacoustic ophthalmoscopy (PAOM) is a novel, hybrid, non-ionizing, and non-invasive imaging technology that has been used to assess the retina. PAOM can provide both anatomic and functional retinal characterizations with high resolution, high sensitivity, high contrast, and a high depth of penetration. Thus, ocular diseases can be precisely detected and visualized at earlier stages, resulting in an improved understanding of pathophysiology, improved management, and the improved monitoring of retinal treatment to prevent vision loss. To better visualize ocular components such as retinal vessels, choroidal vessels, choroidal neovascularization, retinal neovascularization, and the retinal pigment epithelium, an advanced multimodal ocular imaging platform has been developed by a combination of PAOM with other optical imaging techniques such as optical coherence tomography (OCT), scanning laser ophthalmoscopy (SLO), and fluorescence microscopy. The multimodal images can be acquired from a single imaging system and co-registered on the same image plane, enabling an improved evaluation of disease. In this review, the potential application of photoacoustic ophthalmoscopy in both research and clinical diagnosis are discussed as a medical screening technique for the visualization of various ocular diseases. The basic principle and requirements of photoacoustic ocular imaging are introduced. Then, various photoacoustic microscopy imaging systems of the retina in animals are presented. Finally, the future development of PAOM and multimodal imaging is discussed.

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Section: Physical Principle Of Photoacoustic Imagingmentioning

confidence: 99%

Photoacoustic Ophthalmoscopy: Principle, Application, and Future Directions

Nguyen

Paulus

2018

J. Imaging

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“…A striking feature of RP is the appearance of lesions throughout the fundus (Fahim, Daiger & Weleber, 2017). The Optos ® camera (Optos Plc, Dunfermline, Scotland) can acquire wide-angle photographs of the fundus that are suitable for diagnosis, because the device can capture images at a 200° range in a non-mydriatic state with a pupil diameter of two mm (Hu, Liu & Paulus, 2016). Ultrawide-field pseudocolor (UWPC) imaging of optoscopic images is versatile and can also be used in diagnosing diabetic retinopathy, vein occlusion, choroidal masses, uveitis, and other similar diseases (Witmer et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Accuracy of a deep convolutional neural network in detection of retinitis pigmentosa on ultrawide-field images

Masumoto¹,

Tabuchi²,

Nakakura³

et al. 2019

PeerJ

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Evaluating the discrimination ability of a deep convolution neural network for ultrawide-field pseudocolor imaging and ultrawide-field autofluorescence of retinitis pigmentosa. In total, the 373 ultrawide-field pseudocolor and ultrawide-field autofluorescence images (150, retinitis pigmentosa; 223, normal) obtained from the patients who visited the Department of Ophthalmology, Tsukazaki Hospital were used. Training with a convolutional neural network on these learning data objects was conducted. We examined the K-fold cross validation (K = 5). The mean area under the curve of the ultrawide-field pseudocolor group was 0.998 (95% confidence interval (CI) [0.9953–1.0]) and that of the ultrawide-field autofluorescence group was 1.0 (95% CI [0.9994–1.0]). The sensitivity and specificity of the ultrawide-field pseudocolor group were 99.3% (95% CI [96.3%–100.0%]) and 99.1% (95% CI [96.1%–99.7%]), and those of the ultrawide-field autofluorescence group were 100% (95% CI [97.6%–100%]) and 99.5% (95% CI [96.8%–99.9%]), respectively. Heatmaps were in accordance with the clinician’s observations. Using the proposed deep neural network model, retinitis pigmentosa can be distinguished from healthy eyes with high sensitivity and specificity on ultrawide-field pseudocolor and ultrawide-field autofluorescence images.

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“…Scanning laser ophthalmoscopy (SLO) was first described in 1981 [73]. Scanning laser ophthalmoscopy (SLO) uses a single, monochromatic laser with low power and a confocal raster scanning technique to collect an image of the retina and optic nerve head [58,73]. SLO images demonstrate higher contrast than standard fundus camera photos as they can reduce the effect of light scatter.…”

Section: Adaptive Optics (Ao) and Scanning Laser Ophthalmoscopy (Slo)mentioning

confidence: 99%

Advances in Retinal Optical Imaging

Xia

Paulus

2018

Photonics

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Retinal imaging has undergone a revolution in the past 50 years to allow for better understanding of the eye in health and disease. Significant improvements have occurred both in hardware such as lasers and optics in addition to software image analysis. Optical imaging modalities include optical coherence tomography (OCT), OCT angiography (OCTA), photoacoustic microscopy (PAM), scanning laser ophthalmoscopy (SLO), adaptive optics (AO), fundus autofluorescence (FAF), and molecular imaging (MI). These imaging modalities have enabled improved visualization of retinal pathophysiology and have had a substantial impact on basic and translational medical research. These improvements in technology have translated into early disease detection, more accurate diagnosis, and improved management of numerous chorioretinal diseases. This article summarizes recent advances and applications of retinal optical imaging techniques, discusses current clinical challenges, and predicts future directions in retinal optical imaging.

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New Frontiers in Retinal Imaging

Cited by 10 publications

References 76 publications

Photoacoustic Ophthalmoscopy: Principle, Application, and Future Directions

Photoacoustic Ophthalmoscopy: Principle, Application, and Future Directions

Accuracy of a deep convolutional neural network in detection of retinitis pigmentosa on ultrawide-field images

Advances in Retinal Optical Imaging

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