Automatic determination of lung features of CF patients in CT scans
This paper describes a prototype of an automatic system for the detection and evaluation of Cystic fibrosis features (CF) in High resolution computed tomography (HRCT) Scans. The aim of this study lies in presenting this system as a decision support tool for radiologists in future. The CF features t...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2016-09-01
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| Series: | Current Directions in Biomedical Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/cdbme-2016-0115 |
| _version_ | 1818695502546337792 |
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| author | Chaudhuri Tanusree Gong Bo Krueger-Ziolek Sabine Schullcke Benjamin Moeller Knut |
| author_facet | Chaudhuri Tanusree Gong Bo Krueger-Ziolek Sabine Schullcke Benjamin Moeller Knut |
| author_sort | Chaudhuri Tanusree |
| collection | DOAJ |
| description | This paper describes a prototype of an automatic system for the detection and evaluation of Cystic fibrosis features (CF) in High resolution computed tomography (HRCT) Scans. The aim of this study lies in presenting this system as a decision support tool for radiologists in future. The CF features that have been detected and evaluated are Bronchiectasis and Mucus Plugging. This system recognizes Bronchiectasis as the presence of enlarged airways in pulmonary CF-CT slices whereas, Mucus Plugging has been recognized as clusters of high attenuation pixels. The dataset of this study consists of HRCT Scans of five CF patients of varying disease stages. Mean percentages of these CF features that were computed for each intercostal space, starting from the first to the fifth, fairly accurately match the different stages of the disease. |
| first_indexed | 2024-12-17T13:46:30Z |
| format | Article |
| id | doaj.art-dfbc86e103a64bd2a69eac929cd632cb |
| institution | Directory Open Access Journal |
| issn | 2364-5504 |
| language | English |
| last_indexed | 2024-12-17T13:46:30Z |
| publishDate | 2016-09-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Current Directions in Biomedical Engineering |
| spelling | doaj.art-dfbc86e103a64bd2a69eac929cd632cb2022-12-21T21:46:09ZengDe GruyterCurrent Directions in Biomedical Engineering2364-55042016-09-012151952210.1515/cdbme-2016-0115cdbme-2016-0115Automatic determination of lung features of CF patients in CT scansChaudhuri Tanusree0Gong Bo1Krueger-Ziolek Sabine2Schullcke Benjamin3Moeller Knut4Institute of Technical Medicine, Furtwangen University, Villingen-Schwenningen, GermanyInstitute of Technical Medicine, Furtwangen University, Villingen-Schwenningen, GermanyInstitute of Technical Medicine, Furtwangen University, Villingen-Schwenningen, GermanyInstitute of Technical Medicine, Furtwangen University, Villingen-Schwenningen, GermanyInstitute of Technical Medicine, Furtwangen University, Villingen-Schwenningen, GermanyThis paper describes a prototype of an automatic system for the detection and evaluation of Cystic fibrosis features (CF) in High resolution computed tomography (HRCT) Scans. The aim of this study lies in presenting this system as a decision support tool for radiologists in future. The CF features that have been detected and evaluated are Bronchiectasis and Mucus Plugging. This system recognizes Bronchiectasis as the presence of enlarged airways in pulmonary CF-CT slices whereas, Mucus Plugging has been recognized as clusters of high attenuation pixels. The dataset of this study consists of HRCT Scans of five CF patients of varying disease stages. Mean percentages of these CF features that were computed for each intercostal space, starting from the first to the fifth, fairly accurately match the different stages of the disease.https://doi.org/10.1515/cdbme-2016-01152d airway segmentationcomputed tomographycystic fibrosislung segmentationmucus plugging |
| spellingShingle | Chaudhuri Tanusree Gong Bo Krueger-Ziolek Sabine Schullcke Benjamin Moeller Knut Automatic determination of lung features of CF patients in CT scans Current Directions in Biomedical Engineering 2d airway segmentation computed tomography cystic fibrosis lung segmentation mucus plugging |
| title | Automatic determination of lung features of CF patients in CT scans |
| title_full | Automatic determination of lung features of CF patients in CT scans |
| title_fullStr | Automatic determination of lung features of CF patients in CT scans |
| title_full_unstemmed | Automatic determination of lung features of CF patients in CT scans |
| title_short | Automatic determination of lung features of CF patients in CT scans |
| title_sort | automatic determination of lung features of cf patients in ct scans |
| topic | 2d airway segmentation computed tomography cystic fibrosis lung segmentation mucus plugging |
| url | https://doi.org/10.1515/cdbme-2016-0115 |
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