Three-Dimensional Volumetric Renal Reconstruction Based on Geometrical Coefficients

Tomasz Leś , Tomasz Markiewicz , Mirosław Dziekiewicz , Małgorzata Lorent


The article presents an innovative method of 3D computer tomography (CT) image reconstruction of kidney. Diagnosis based on CT scanning allows to obtain projections of multi-dimensional object, made from different directions in order to create cross-sectional (2D) slices. Standard techniques for identifying kidneys in CT images analyze each 2D slice separately. It causes different reconstruction accuracy for the same object at its different heights. This is the main problem of a machine-learning systems. Reconstruction error of end-slices of the kidney model is often greater than the error of the kidney's middle part. The main idea of the technique presented in this paper is to analyze the largest coherent 3D spatial-areas. This technique allows to increase the accuracy of kidney detection as well as to decrease the FP (false positive) error. An additional advantage of the developed algorithm is the possibility of obtaining a precise model representing the 3D view of an entire kidney.

Author Tomasz Leś (FoEE / ITEEMIS)
Tomasz Leś,,
- The Institute of the Theory of Electrical Engineering, Measurement and Information Systems
, Tomasz Markiewicz (FoEE / ITEEMIS)
Tomasz Markiewicz,,
- The Institute of the Theory of Electrical Engineering, Measurement and Information Systems
, Mirosław Dziekiewicz
Mirosław Dziekiewicz,,
, Małgorzata Lorent
Małgorzata Lorent,,
Journal seriesStudies in Health Technology and Informatics, ISSN 0926-9630, e-ISSN 1879-8365
Issue year2020
Publication size in sheets0.5
Keywords in Englishgeometrical-coefficients; reconstruction; renal
ASJC Classification2718 Health Informatics; 3605 Health Information Management; 2204 Biomedical Engineering
Languageen angielski
LicenseJournal (articles only); author's original; Uznanie Autorstwa - Użycie Niekomercyjne (CC-BY-NC); after publication
WUT3e0f24910a4c479da265a207a1aa8d4a.pdf 411.6 KB
Score (nominal)5
Score sourcejournalList
ScoreMinisterial score = 5.0, 10-09-2020, ArticleFromJournal
Publication indicators Scopus Citations = 0; Scopus SNIP (Source Normalised Impact per Paper): 2018 = 0.326
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