Correction

This article refers to:

Impact of a generalised SVG-based large-scale super-resolution algorithm on the design of light-weight medical image segmentation DNNs

Article title: Impact of a generalised SVG-based large-scale super-resolution algorithm on the design of light-weight medical image segmentation DNNs

Authors: Mina Esfandiarkhani and Amir Hossein Foruzan

Journal: Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization

DOI: http://dx.doi.org/ 10.1080/21681163.2023.2266008

This article was initially published with some errors in few sentence, this has been updated now.

• 1. The sentence below Equation (1) has been revised to:

In Equation (1), is the number of classes, N is the number of pixels, $y_{\mathit{k},\mathit{i}}$ is the true mask, and $\text{~}{y}_{\mathit{k},\mathit{i}}$ is the automatic mask.

• 2. Second sentence of “4.1 Dataset” section has been revised to:

They were liver and lung Computed Tomography and prostate Magnetic Resonance images.

• 3. Section 3, Page 5, Left Column, Last Paragraph: “We select AccessisdeniedAccessisdenied boundary points (AccessisdeniedAccessisdenied) and represent them as a polynomial of degree AccessisdeniedAccessisdenied (AccessisdeniedAccessisdenied).” was be replaced by “We select p boundary points (5≤p≤10) and represent them as a polynomial of degree n (2≤n≤5).”