Computer-Aided Diagnosis of Pneumoperitoneum on Neonatal Abdominal Radiographs
The DCNN model demonstrated robust segmentation and classification performance, highlighting its potential as a clinical decision support tool for early detection of gastrointestinal perforation in neonates. Future studies should validate the model's generalizability and assess its integration into clinical practice.
Authors
- Yayoi Miyazono (ORCID: https://orcid.org/0000-0001-6195-0737)
- Takahiro Hosokawa (ORCID: https://orcid.org/0000-0001-9523-4077)
- Mikihiro Inoue (ORCID: https://orcid.org/0000-0003-4573-0405)
- Yohei Sanmoto (ORCID: https://orcid.org/0000-0001-5006-2507)
- Boyuan Peng (ORCID: https://orcid.org/0009-0002-9226-6406)
- Kouji Masumoto (ORCID: https://orcid.org/0000-0002-0312-9403)
- Ruiyao Zhang (ORCID: https://orcid.org/0009-0003-8760-3452)
- Xin Zhu
- Yasuhiro Kondo
Institutions
- University of Aizu (JP)
- Fujita Health University (JP)
- University of Tsukuba (JP)
- Beijing Chao-Yang Hospital, Capital Medical University (CN)
- Saitama Children's Medical Center (JP)
- University of Tsukuba Hospital (JP)
- Japan Research Institute (JP)
- Beijing Chaoyang Emergency Medical Center (CN)
Publication Details
- Journal
- Neonatology
- Published
- 2025-11-28
- DOI
- https://doi.org/10.1159/000549186
- Primary Topic
- Appendicitis Diagnosis and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00