34 research outputs found
Challenges of 3D Surface Reconstruction in Capsule Endoscopy
There are currently many challenges specific to three-dimensional (3D)
surface reconstruction using capsule endoscopy (CE) images. There are also
challenges specific to viewing the content of CE reconstructed 3D surfaces for
bowel disease diagnosis purposes. In this preliminary work, the author focuses
on the latter and discusses the effects such challenges have on the content of
reconstructed 3D surfaces from CE images. Discussions are divided into two
parts. The first part focuses on the comparison of the content of 3D surfaces
reconstructed using both preprocessed and non-preprocessed CE images. The
second part focuses on the comparison of the content of 3D surfaces viewed at
the same azimuth angles and different elevation angles of the line of sight.
Experiments-based conclusion suggests 3D printing as a solution to the line of
sight and 2D screen visual restrictions.Comment: 5 pages, 3 figure
Normalized Weighting Schemes for Image Interpolation Algorithms
This paper presents and evaluates four weighting schemes for image
interpolation algorithms. The first scheme is based on the normalized area of
the circle, whose diameter is equal to the minimum side of a tetragon. The
second scheme is based on the normalized area of the circle, whose radius is
equal to the hypotenuse. The third scheme is based on the normalized area of
the triangle, whose base and height are equal to the hypotenuse and virtual
pixel length, respectively. The fourth weighting scheme is based on the
normalized area of the circle, whose radius is equal to the virtual pixel
length-based hypotenuse. Experiments demonstrated debatable algorithm
performances and the need for further research.Comment: 8 pages, 14 figure
Aliasing artefact index for image interpolation quality assessment
A preliminary study of a non-reference aliasing artefact index (AAI) metric is presented in this paper. We focus on the effects of combining a full-reference metric and interpolation algorithm. The nearest neighbor algorithm (NN) is used as the gold standard against which test-algorithms are judged in terms of aliased structures. The structural similarity index (SSIM) metric is used to evaluate a test image (i.e. a test-algorithm's image) and a reference image (i.e. the NN's image). Preliminary experiments demonstrated promising effects of the AAI metric against state-of-the-art non-reference metrics mentioned. A new study may further develop the studied metric for potential applications in image quality adaptation and/or monitoring in medical imaging