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Improvement in Disease Diagnosis in Computed Tomography Images by Correlating Organ Volumes with Disease Occurrences in Humans
- In this paper, we investigate the influence of different disease groups on the size of different 1 anatomical structures. To this end, we first modify and improve an existing anatomical segmentation 2 model. Then, we use this model to segment 104 anatomical structures from computed tomography 3 (CT) scans and compute their volumes from the segmentation. After correlating the results with each 4 other, we find no new significant correlations. After correlating the volume data with known diseases 5 for each case, we find two weak correlations, one of which has not been described before and for 6 which we present a possible explanation.
Author: | Timo van Meegdenburg, Jens Kleesiek, Jan Egger, Sören Perrey |
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DOI: | https://doi.org/10.3390/biomedinformatics3030036 |
Parent Title (English): | BioMedInformatics |
Editor: | Alexandre G. De Brevern |
Document Type: | Article |
Language: | English |
Date of Publication (online): | 2023/12/19 |
Date of first Publication: | 2023/07/05 |
Publishing Institution: | Westfälische Hochschule Gelsenkirchen Bocholt Recklinghausen |
Release Date: | 2024/01/26 |
Tag: | Segmentation; Correlation; Diseases; Convolutional Neural Networks |
Volume: | 2023 |
Issue: | 3/3 |
First Page: | 1 |
Last Page: | 18 |
Departments / faculties: | Institute |
Licence (German): | Creative Commons - Namensnennung - Nicht kommerziell |