Optimal Atlas Segmentation on CT Images for Diagnosis of Pediatric Mycoplasma Pneumonia
| Autor: | Hongbo Li, Chunhong Cheng, Junyan Wang, Liang Wang |
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| Rok vydání: | 2021 |
| Předmět: |
Article Subject
Pleural effusion business.industry Image quality 030204 cardiovascular system & hematology medicine.disease Computer Science Applications Diagnosis methods QA76.75-76.765 03 medical and health sciences 0302 clinical medicine medicine.anatomical_structure Feature (computer vision) Atlas (anatomy) Clinical diagnosis Mycoplasma pneumonia medicine Segmentation Computer software 030212 general & internal medicine Nuclear medicine business Software |
| Zdroj: | Scientific Programming, Vol 2021 (2021) |
| ISSN: | 1875-919X 1058-9244 |
| DOI: | 10.1155/2021/2586956 |
| Popis: | This work aimed to explore the clinical application value of CT imaging technology based on the optimal Atlas segmentation algorithm (OASA) in the diagnosis of pediatric mycoplasma pneumonia (MP). Eighty-eight children with MP were selected and divided into group A (CT image based on the OASA) and group B (chest X-ray) according to the diagnosis methods. The detection rate, image feature performance, and image quality satisfaction of the two groups of children were compared. The results showed that the detection rate of group A was 97.73% and that of group B was 95.46%, and there was no considerable difference between the two ( P > 0.05). The pleural effusion detection rate of children in group A was evidently superior to that of X-ray group, while the increased bronchovascular shadows’ detection rate was greatly inferior to that of X-ray group ( P P > 0.05). CT image quality satisfaction (98.50%) was higher versus X-ray (79.46%) ( P |
| Databáze: | OpenAIRE |
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