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| Content Provider | Springer Nature : BioMed Central |
|---|---|
| Author | Birk, Gerald Kästle, Marc Tilp, Cornelia Stierstorfer, Birgit Klee, Stephan |
| Abstract | Background One of the main diagnostic tools for lung diseases in humans is computed tomography (CT). A miniaturized version, micro-CT (μCT) is utilized to examine small rodents including mice. However, fully automated threshold-based segmentation and subsequent quantification of severely damaged lungs requires visual inspection and manual correction. Methods Here we demonstrate the use of densitometry on regions of interest (ROI) in automatically detected portions of the lung, thus avoiding the need for lung segmentation. Utilizing deep learning approaches, the middle part of the lung is found in a μCT-stack and a ROI is placed in the left and the right lobe. Results The intensity values within the ROIs of the μCT images were collected and subsequently used for the calculation of different lung-related parameters, such as mean lung attenuation (MLA), mode, full width at half maximum (FWHM), and skewness. For validation, the densitometric approach was correlated with histological readouts (Ashcroft Score, Mean Linear Intercept). Conclusion We here show an automated tool that allows rapid and in-depth analysis of μCT scans of different murine models of lung disease. |
| Related Links | https://respiratory-research.biomedcentral.com/counter/pdf/10.1186/s12931-020-01370-8.pdf |
| Ending Page | 8 |
| Page Count | 8 |
| Starting Page | 1 |
| File Format | HTM / HTML |
| DOI | 10.1186/s12931-020-01370-8 |
| Journal | Respiratory Research |
| Issue Number | 1 |
| Volume Number | 21 |
| Language | English |
| Publisher | BioMed Central |
| Publisher Date | 2020-05-24 |
| Access Restriction | Open |
| Subject Keyword | Pneumology Respiratory System Pneumology/Respiratory System |
| Content Type | Text |
| Resource Type | Article |
| Subject | Pulmonary and Respiratory Medicine |
| Journal Impact Factor | 4.7/2023 |
| 5-Year Journal Impact Factor | 5.3/2023 |
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