A) Main steps of the segmentation algorithm. The operations presented in square blocks are always performed, while that in the elliptic block is optional. B) Main steps of the OCT pullback quality assessment. The operation reported in the dashed box are performed only once on the manual segmentation, while the others are performed for every pullback. The output of each step is always written in italic.</p
The section indicated by the red rectangle indicates the embarrassingly parallel part of the algorit...
Since all metric results take values between 0 and 1, relatively high and stable values of Recall an...
Investigated factors are model architecture, tiling method (FS = fixed-stride, OBP = object-based po...
<p>Green area in the top and left middle are ROI and the red arrows show some representatives of loa...
We overview the existing OCT work, especially the practical aspects of it. We create a novel algorit...
<p>Flowchart showing the major steps of the semi-automated segmentation algorithm.</p
<p>The light green dashed circle indicates the holes in the binarization step, and the light yellow ...
Comparisons are made among automatic segmentation (AUTO) and manual segmentations (R1 and R2). A-C) ...
Quantitative testing of segmentation algorithms implies rigorous testing against ground-truth segmen...
<p>Flowcharts showing the steps involved in (a) data processing, segmentation and feature extraction...
Image segmentation is a method to extract regions of interest from an image. It remains a fundamenta...
This document describes an efficient enhancement of the waterfall algorithm, a hierarchical segmenta...
Column segmentation logically precedes OCR in the document analysis process. The trainable algorithm...
The purpose of this paper is to describe a framework for evaluating image segmentation algorithms. I...
This paper tackles the supervised evaluation of image segmentation and object proposal algorithms. I...
The section indicated by the red rectangle indicates the embarrassingly parallel part of the algorit...
Since all metric results take values between 0 and 1, relatively high and stable values of Recall an...
Investigated factors are model architecture, tiling method (FS = fixed-stride, OBP = object-based po...
<p>Green area in the top and left middle are ROI and the red arrows show some representatives of loa...
We overview the existing OCT work, especially the practical aspects of it. We create a novel algorit...
<p>Flowchart showing the major steps of the semi-automated segmentation algorithm.</p
<p>The light green dashed circle indicates the holes in the binarization step, and the light yellow ...
Comparisons are made among automatic segmentation (AUTO) and manual segmentations (R1 and R2). A-C) ...
Quantitative testing of segmentation algorithms implies rigorous testing against ground-truth segmen...
<p>Flowcharts showing the steps involved in (a) data processing, segmentation and feature extraction...
Image segmentation is a method to extract regions of interest from an image. It remains a fundamenta...
This document describes an efficient enhancement of the waterfall algorithm, a hierarchical segmenta...
Column segmentation logically precedes OCR in the document analysis process. The trainable algorithm...
The purpose of this paper is to describe a framework for evaluating image segmentation algorithms. I...
This paper tackles the supervised evaluation of image segmentation and object proposal algorithms. I...
The section indicated by the red rectangle indicates the embarrassingly parallel part of the algorit...
Since all metric results take values between 0 and 1, relatively high and stable values of Recall an...
Investigated factors are model architecture, tiling method (FS = fixed-stride, OBP = object-based po...