Originalartikel | erschienen - Druck | peer reviewed | Open Access
A deep cascaded segmentation of obstructive sleep apnea-relevant organs from sagittal spine MRI.
International Journal of Computer Assisted Radiology and Surgery
2021 ;
16(4):
579 - 588
http://www.ncbi.nlm.nih.gov/pubmed/33770362[PubMed]
Bibliometric indicators
Impact Factor = 3.421
Citations (WOS) = 3
DOI = 10.1007/s11548-021-02333-0
PubMed-ID = 33770362
Affiliations
Abstract
Purpose: The main purpose of this work was to develop an efficient approach for segmentation of structures that are relevant for diagnosis and treatment of obstructive sleep apnea syndrome (OSAS), namely pharynx, tongue, and soft palate, from mid-sagittal magnetic resonance imaging (MR) data. This framework will be applied to big data acquired within an on-going epidemiological study from a general population.
Methods: A deep cascaded framework for subsequent segmentation of pharynx, tongue, and soft palate is presented. The pharyngeal structure was segmented first, since the airway was clearly visible in the T1-weighted sequence. Thereafter, it was used as an anatomical landmark for tongue location. Finally, the soft palate region was extracted using segmented tongue and pharynx structures and used as input for a deep network. In each segmentation step, a UNet-like architecture was applied.
Results: The result assessment was performed qualitatively by comparing the region boundaries obtained from the expert to the framework results and quantitatively using the standard Dice coefficient metric. Additionally, cross-validation was applied to ensure that the framework performance did not depend on the specific selection of the validation set. The average Dice coefficients on the test set were [Formula: see text], [Formula: see text], and [Formula: see text] for tongue, pharynx, and soft palate tissues, respectively. The results were similar to other approaches and consistent with expert readings.
Conclusion: Due to high speed and efficiency, the framework will be applied for big epidemiological data with thousands of participants acquired within the Study of Health in Pomerania as well as other epidemiological studies to provide information on the anatomical structures and aspects that constitute important risk factors to the OSAS development.
Published in
International Journal of Computer Assisted Radiology and Surgery
Year | 2021 |
Impact Factor (2021) | 3.421 |
Volume | 16 |
Issue | 4 |
Pages | 579 - 588 |
Open Access | ja |
Peer reviewed | ja |
Article type | Originalartikel |
Article state | erschienen - Druck |
DOI | 10.1007/s11548-021-02333-0 |
PubMed-ID | 33770362 |
Common journal data
Short name: INT J COMPUT ASS RAD
ISSN: 1861-6410
eISSN: 1861-6429
Country: GERMANY (FED REP GER)
Language: English
Categories:
Impact factor trend
ISSN: 1861-6410
eISSN: 1861-6429
Country: GERMANY (FED REP GER)
Language: English
Categories:
- SURGERY
- ENGINEERING, BIOMEDICAL
- RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Impact factor trend
Year | Impact Factor |
---|---|
2011 | 1.481 |
2012 | 1.364 |
2013 | 1.659 |
2014 | 1.707 |
2015 | 1.827 |
2016 | 1.863 |
2017 | 1.961 |
2018 | 2.155 |
2019 | 2.473 |
2020 | 2.924 |
2021 | 3.421 |