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Applications of Optical Coherence Tomography in the Ocular Diagnosis: From the Tear Film to the Sclera
 
 
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Correction to Diagnostics 2021, 11(12), 2319.
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Correction

Correction: Rizzo et al. Artificial Intelligence and OCT Angiography in Full Thickness Macular Hole. New Developments for Personalized Medicine. Diagnostics 2021, 11, 2319

by
Stanislao Rizzo
1,2,3,†,
Alfonso Savastano
1,2,†,
Jacopo Lenkowicz
4,*,
Maria Cristina Savastano
1,2,
Luca Boldrini
2,4,
Daniela Bacherini
5,
Benedetto Falsini
1,2 and
Vincenzo Valentini
2,4
1
Ophthalmology Unit, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
2
Ophthalmology Unit, Catholic University “Sacro Cuore”, 00168 Rome, Italy
3
Consiglio Nazionale delle Ricerche (CNR), Istituto di Neuroscienze, 56024 Pisa, Italy
4
Radiation Oncology Unit, Fondazione Policlinico Universitario “A. Gemelli” IRCCS, 00168 Rome, Italy
5
Department of Neurosciences, Psychology, Drug Research and Child Health Eye Clinic, University of Florence, AOU Careggi, 50139 Florence, Italy
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Diagnostics 2022, 12(7), 1593; https://doi.org/10.3390/diagnostics12071593
Submission received: 9 June 2022 / Accepted: 21 June 2022 / Published: 30 June 2022
(This article belongs to the Special Issue Applications of Optical Coherence Tomography in the Ocular Diagnosis: From the Tear Film to the Sclera)
Versions Notes

Figure Legend

In the original publication [1], there was a mistake in the legend for Figure 8. Values for C1 and C2 were inverted. The correct legend appears below.
Figure 8 legend becomes:
Clustering analysis from Inception V3 deep learning features based on combined superficial and deep OCT-As. The mean 1-year BVCA for C1 and C2 was 66.67 and 49.1, respectively, with a t-test p-value equal to 0.005.

Error in Table

In the original publication, there was a mistake in Table 2 as published. Values for C1 and C2 were inverted. The corrected Table 2 appears below.
Table
Table 2. Distribution of 1-year visual acuity score in the two image clusters for the different CNN types. * p < 0.05; ** p < 0.01.
Table 2. Distribution of 1-year visual acuity score in the two image clusters for the different CNN types. * p < 0.05; ** p < 0.01.
CNN TypeImage Type1-Year Visual Acuity Mean (Standard Deviation)—Cluster 11-Year Visual Acuity Mean (Standard Deviation)—Cluster 2t-Test p-Value
Inception V3Superficial Images59.64 (18.40)51.52 (20.50)0.252
Deep Images61.70 (17.20)49.87 (20.50)0.081
Superficial + Deep Images66.67 (16.00)49.10 (18.60)0.005 **
VGG-16Superficial Images62.29 (15.90)52.86 (20.80)0.139
Deep Images59.96 (17.6)43.29 (21.40)0.092
Superficial + Deep Images63.85 (15.40)52.36 (20.50)0.070
VGG-19Superficial Images67.80 (11.90)52.16 (20.20)0.008 **
Deep Images60.50 (18.20)45.44 (19.20)0.060
Superficial + Deep Images59.92 (14.00)54.91 (21.70)0.416
SqueezeNetSuperficial Images59.03 (18.00)45.00 (22.40)0.196
Deep Images---
Superficial + Deep Images66.90 (13.4)52.52 (20.10)0.021 *

Text Correction

There was an error in the original publication. Values for C1 and C2 were inverted.
A correction has been made to Abstract, sentence: best-corrected visual acuity (BCVA) C1 = 49.10 (18.60 SD) and BCVA C2 = 66.67 (16.00 SD, p = 0.005)
The sentence becomes:
best-corrected visual acuity (BCVA) C1 = 66.67 (16.00 SD) and BCVA C2 = 49.10 (18.60 SD, p = 0.005).
A correction has been made to Results, Paragraph 9, sentence: In this configuration, the mean of letters for C1 and C2 was 49.1 and 66.67, respectively, with a t-test p-value equal to 0.005 (Figure 8)
The sentence becomes:
In this configuration, the mean of letters for C1 and C2 was 66.67 and 49.1, respectively, with a t-test p-value equal to 0.005 (Figure 8).
The authors apologize for any inconvenience caused and state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated.

Reference

  1. Rizzo, S.; Savastano, A.; Lenkowicz, J.; Savastano, M.C.; Boldrini, L.; Bacherini, D.; Falsini, B.; Valentini, V. Artificial Intelligence and OCT Angiography in Full Thickness Macular Hole. New Developments for Personalized Medicine. Diagnostics 2021, 11, 2319. [Google Scholar] [CrossRef] [PubMed]
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MDPI and ACS Style

Rizzo, S.; Savastano, A.; Lenkowicz, J.; Savastano, M.C.; Boldrini, L.; Bacherini, D.; Falsini, B.; Valentini, V. Correction: Rizzo et al. Artificial Intelligence and OCT Angiography in Full Thickness Macular Hole. New Developments for Personalized Medicine. Diagnostics 2021, 11, 2319. Diagnostics 2022, 12, 1593. https://doi.org/10.3390/diagnostics12071593

AMA Style

Rizzo S, Savastano A, Lenkowicz J, Savastano MC, Boldrini L, Bacherini D, Falsini B, Valentini V. Correction: Rizzo et al. Artificial Intelligence and OCT Angiography in Full Thickness Macular Hole. New Developments for Personalized Medicine. Diagnostics 2021, 11, 2319. Diagnostics. 2022; 12(7):1593. https://doi.org/10.3390/diagnostics12071593

Chicago/Turabian Style

Rizzo, Stanislao, Alfonso Savastano, Jacopo Lenkowicz, Maria Cristina Savastano, Luca Boldrini, Daniela Bacherini, Benedetto Falsini, and Vincenzo Valentini. 2022. "Correction: Rizzo et al. Artificial Intelligence and OCT Angiography in Full Thickness Macular Hole. New Developments for Personalized Medicine. Diagnostics 2021, 11, 2319" Diagnostics 12, no. 7: 1593. https://doi.org/10.3390/diagnostics12071593

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