ライフサイエンスコーパス: fundus image

1 lar fundus image to the peripapillary ocular fundus image.

2 stance of 2.5 cm was set with a good quality fundus image.

3 optic nerve head were clearly visible on the fundus images.

4 y on phenotypical characteristics from color fundus images.

5 100 degrees field-of-view, composite retinal fundus images.

6 that do not require subjective evaluation of fundus images.

7 al filtering, and thresholding of the colour fundus images.

8 in and/or modulate the observed AF signal in fundus images.

9 normality in 25/26 (96.2%) of the ungradable fundus images.

10 re sensitive than that of nonmydriatic color fundus images.

11 easure the vessel widths at branch points in fundus images.

12 moscope for high-resolution confocal retinal fundus imaging.

13 Retinopathy was evaluated from digital fundus images (2002-2006) using the modified Airlie Hous

14 patients with type 1 diabetes and ungradable fundus images, 361 participants were included in the ana

15 common reasons for referral were ungradable fundus image (39.3% of those referred), best-corrected V

16 Twenty-six fundus images (5.5%) were ungradable.

17 An OCT fundus image, akin to a fundus photograph was generated

18 OCT fundus images allow precise registration of OCT images a

19 andard diagnosis when interpreting the color fundus images alone versus interpreting the color fundus

20 conventional AAV2 in GFP expression based on fundus image analysis and qRT-PCR.

21 OCT fundus images and 3D visualizations were generated with

22 d strengths of both the remote evaluation of fundus images and bedside clinical examination of infant

23 The algorithm processed color fundus images and classified them as healthy (no retinop

24 r exposure to OIR, which was visible in live fundus images and fixed whole-mounted retinas.

25 For each eye, two undilated 45 degrees fundus images and four undilated volume OCT image sets c

26 Fundus images and OCT scans were successfully acquired i

27 the acquisition of two undilated 45 degrees fundus images and two undilated raster 3D-OCT scans (512

28 in the study, 9962 (99.3%) who had gradable fundus images and Visual Function Index (VF-11) data ava

29 usen (RPD) was assessed by masked grading of fundus images and was confirmed with optical coherence t

30 onfocal scanning laser ophthalmoscopy (cSLO) fundus imaging and "eye-tracked" spectral-domain optical

31 Thresholds were evaluated by fundus imaging and angiography.

32 Live fundus imaging and fluorescein angiography at P17 were c

33 The degree of laser burns was confirmed by fundus imaging and histology.

34 In vivo fluorescent fundus imaging and immunofluorescent confocal microscopy

35 Compared with studies using fundus imaging and international classification systems,

36 Fundus imaging and microscopic analysis indicated that K

37 FP expression was noninvasively monitored by fundus imaging and retinal expression was analyzed 4 wee

38 OCT), near-infrared reflectance (NIR), color fundus images, and medical charts were reviewed.

39 OP]) was developed using a set of 77 digital fundus images, and the system was designed to classify i

40 their axons in the retina was determined by fundus imaging, and axonal degeneration in the optic ner

41 optical coherence tomography (OCT), infrared fundus imaging, and biomicroscopy were performed at base

42 The clinical details, digital fundus imaging, and treatment details and outcomes also

43 pert fundus grading of 468 patients and 2145 fundus images are: 98.6% and 96.3% when classifying cate

44 ll participants underwent color, FAF, and IR fundus imaging, as well as imaging with a prototype Zeis

45 rnational Classification System on digitized fundus images at 1 grading center.

46 a: (1) complete clinical records and digital fundus images at baseline and follow-up visits, (2) posi

47 s underwent standard ophthalmic examination, fundus imaging, autofluorescence testing, Goldmann visua

48 ngs and 100 vein branchings selected from 50 fundus images by comparing with vessel width measurement

49 rning-based automated assessment of AMD from fundus images can produce results that are similar to hu

50 tic red-free monochromatic 60-degree digital fundus images centered on the macula and optic disc of 2

51 A fundus image dataset from 14 patients (200 fundus images

52 hm was evaluated on two publically available fundus-image datasets comprising 258 images (160 AMD and

53 Fundus imaging demonstrated that R172W mice developed se

54 rol the position of the OCT beam spot on the fundus image display.

55 s of a semiautomated optical head to acquire fundus images, evaluate visual acuity, and transmit the

56 athy (DR) was diagnosed by capturing 7-field fundus images, evaluated by two independent ophthalmolog

57 bright lesions (drusen and flecks) in their fundus images, even when the images were visually select

58 fluorescein angiogram (FA) or red-free (RF) fundus images; fluorescein angiography was used in this

59 p, highlighting subregions within each input fundus image for further clinical review.

60 erized by systematic review of all available fundus images for each patient, including color photogra

61 ties of 3D-OCT were higher than nonmydriatic fundus images for overall detection of retinal abnormali

62 econstructing a wide-angle composite retinal fundus image from a set of adjacent small- and wide-angl

63 Fundus images from 43 monozygotic (MZ) and 32 dizygotic

64 Fundus images from 58 eyes (in 58 patients) with interme

65 A total of 75 137 publicly available fundus images from diabetic patients were used to train

66 s using a reading center to evaluate retinal fundus images from infants at risk for retinopathy of pr

67 (e-ROP) Study telemedicine system of remote fundus image grading and The Children's Hospital of Phil

68 w that the methodology used for grading CATT fundus images has good reproducibility.

69 lar telangiectasia type 2 in whom multimodal fundus imaging identified neuronal features without clin

70 edly suppressed angiogenesis as evaluated by fundus imaging in aged Ins2(Akita) mice even after 3mont

71 Fundus imaging included color photography, red-free imag

72 terized by systematic analysis of multimodal fundus imaging, including color photographs, fundus auto

73 mination, fundus photography, and multimodal fundus imaging, including Fourier-domain optical coheren

74 idth relationship at vessel branch points in fundus images is an important biomarker of retinal and s

75 AO fundus imaging is a reliable technique for assessing and

76 tual fixation as assessed under simultaneous fundus imaging, its correlation with the established exp

77 been biased by the effect of axial length on fundus image magnification and, therefore, both measured

78 t are not generally visible with traditional fundus imaging modalities.

79 es using alternative classifications without fundus imaging most likely to diagnose late AMD (OR, 2.9

80 nts were at risk for developing AMD based on fundus images obtained at baseline visits.

81 ular degeneration was easily identified from fundus images obtained from the low-cost camera.

82 ive hundred and one sets of 3D-OCT scans and fundus images of 395 eyes of 223 patients were found in

83 al imaging and scanning laser ophthalmoscopy fundus images of all three Crb1(rd8/rd8) lines showed a

84 ocal scanning laser ophthalmoscope (cSLO) AF fundus images of normal maculae were obtained from both

85 Three hundred thirty-five fundus images of prematurely born infants were obtained

86 d in 2007 and 2016 to classify 34 wide-field fundus images of ROP as plus, pre-plus, or normal, coded

87 V2 produced visible transduction, as seen in fundus images, only when the retina was altered by gangl

88 PE- defects in patients with AMD using Color fundus images, Optical coherence tomography (OCT), OCT-A

89 resence of definite irregularities on either fundus imaging or OCT by eye in this asymptomatic popula

90 s who had digital autofluorescence and color fundus imaging performed at the University of Michigan K

91 n order to obtain detectable signal with low fundus image quality (suboptimal setting) while in the s

92 Annual fundus image sets from 114 CAPT patients who developed G

93 Normal AF fundus images show finely resolved, concentric, elliptic

94 essment of composite OCT scans and composite fundus images showed little motion artifact or blurring

95 OCT fundus images similar to those acquired with a scanning

96 igital image file compression and decreasing fundus image spatial resolution led to skewed measuremen

97 ophthalmologist masked to the results of the fundus images subsequently examined each eye with indire

98 Early or late AMD, assessed through fundus images taken through dilated pupils using a 45 de

99 Fundus images, taken using a digital camera through dark

100 , validate, and correlate topical endoscopic fundus imaging (TEFI) with histologic features of murine

101 feature after registering the macular ocular fundus image to the peripapillary ocular fundus image.

102 ize color and nonuniform illumination of the fundus images to define a region of interest and to iden

103 methods for automatically detecting AMD from fundus images using a novel application of deep learning

104 Autofluorescence fundus imaging using an adaptive optics scanning laser o

105 sual acuity (VA), best-corrected VA, digital fundus imaging, visual field testing, and measurement of

106 For each eye, the 2 fundus images were aligned using Heidelberg's AutoRescan

107 n in two central macular regions on baseline fundus images were determined using an image analysis al

108 Composite OCT scans and composite fundus images were generated for assessment of eye track

109 Fundus images were graded for AMD using the Wisconsin Ag

110 Fundus images were graded for the presence of peripapill

111 Fundus images were graded using the International Classi

112 Drusen area measurements on color fundus images were larger than those with SD-OCT scans.

113 ectroretinographic (ERG) records and digital fundus images were obtained at P20 +/- 1, P30 +/- 1, and

114 The color fundus images were registered to the OCT data set and me

115 plore image compression, 40 natively digital fundus images were selected with good photo quality, hig

116 Digital color fundus images were taken on the same day.

117 Paired monochromatic and autofluorescence fundus images were used for detailed analysis of the top

118 Replacement of film fundus images with digital images for DR severity level

119 single, foveal nonmydriatic 45 degrees color fundus imaging with 3D-OCT-1000 in a 4 month-period were

120 tional classification systems, studies using fundus imaging with alternative classifications were mor

121 A fundus image dataset from 14 patients (200 fundus images, with an average of 14 images per patient)