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23 May 2022 Unsupervised super-resolution reconstruction of hyperspectral histology images for whole-slide imaging (Errata)
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Abstract

Corrections to the published article include values in Table 1 and provision of an omitted reference.

This article [J. Biomed. Opt. 27(5), 056502 (2022) doi: 10.1117/1.JBO.27.5.056502 was originally published on 16 May 2022 with the following errors:

  • 1. The wavelength range in Section 2.1 was misstated as 480 to 720 nm; the correct wavelength range is 470 to 720 nm.

  • 2. Values in Table 1 representing the numbers of patches in the hyperspectral histologic dataset were incorrectly reported as follows:

Original:

Table 1

Summary of the hyperspectral histologic dataset.

Patient IDOrganNumber of imagesNumber of patches
T slideN slideTotalCancerousNormalTotal
1Larynx584210016,667975626,423
2Hypopharynx954514021,04017,35038,390
3Larynx386210010,077956319,640
4Larynx2228503949817112,120
5Larynx58238114,526550820,034
6Larynx291039690321399042
7Larynx2816447087299210,079
8Buccal mucosa231235488818416729
9Larynx2037573979819912,178
10Larynx131932311146047715
11Larynx53247713,573367117,244
12Larynx231740537526948069
13Larynx58288616,318640122,719
14Larynx46287412,263651818,781
15Larynx3517528750423812,988
16Larynx814012120,00210,07330,075
Total6804481128168,508103,718272,226

Corrected:

Patient IDOrganNumber of imagesNumber of patches
T slideN slideTotalCancerousNormalTotal
1Larynx584210016,444975626,200
2Hypopharynx954514021,04017,35038,390
3Larynx386210011,07716,92428,001
4Larynx2228505015681911,834
5Larynx58238114,526550820,034
6Larynx291039690321399042
7Larynx2816447087299210,079
8Buccal mucosa231235488818416729
9Larynx2037573979819912,178
10Larynx131932311146047715
11Larynx53247713,573367117,244
12Larynx231740537526948069
13Larynx58288616,318640122,719
14Larynx46287412,519651819,037
15Larynx3517528750423812,988
16Larynx814012120,00210,07330,075
Total6804481128170,607109,727280,334

  • 3. A reference was omitted: K. He et al., “Delving deep into rectifiers: surpassing human-level performance on ImageNet Classification,” Proc. IEEE International Conference on Computer Vision, 1026-1034, (2015). The reference was added as Ref. 39; Refs. 39-45 were changed to Refs. 40-46.

These errors were corrected on 18 May 2022.

© The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Ling Ma, Armand Rathgeb, Hasan Mubarak, Minh Tran, and Baowei Fei "Unsupervised super-resolution reconstruction of hyperspectral histology images for whole-slide imaging (Errata)," Journal of Biomedical Optics 27(5), 059801 (23 May 2022). https://doi.org/10.1117/1.JBO.27.5.059801
Published: 23 May 2022
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KEYWORDS
Hyperspectral imaging

Super resolution

Computer vision technology

Image classification

Machine vision

Precision measurement

Radiology

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