Back to all papers

Multi-dimensional deep learning-based segmentation and volumetric assessment of sphenoid sinus fluid on postmortem CT in drowning cases.

March 17, 2026pubmed logopapers

Authors

Heo JH,Kim MJ,Jang SJ,Lee J,Im SB,Lee S,Na JY,Kim Y,Yoon Y,Kwon JH

Affiliations (6)

  • Forensic Medicine Division, National Forensic Service Busan Institute, Yangsan, Republic of Korea.
  • Department of Forensic Medicine, Pusan National University School of Medicine, Yangsan, Republic of Korea.
  • Division of Postmortem Investigation, National Forensic Service, Wonju, Republic of Korea.
  • Department of Multidisciplinary Radiological Science, The Graduate School of Dongseo University, Busan, Republic of Korea.
  • Department of Multidisciplinary Radiological Science, The Graduate School of Dongseo University, Busan, Republic of Korea. [email protected].
  • Forensic Medicine Division, National Forensic Service Busan Institute, Yangsan, Republic of Korea. [email protected].

Abstract

Sphenoid sinus fluid is considered a supportive indicator of drowning in forensic medicine, but traditional manual assessment on postmortem computed tomography (PMCT) is labor-intensive and observer-dependent. Efficient, reproducible methods for quantitative evaluation are needed in forensic practice. This study developed deep learning-based approaches for the automated segmentation and volumetric estimation of sphenoid sinus fluid using PMCT images from 165 autopsy-confirmed drowning cases. Three U-Net-based models (2D, 2.5D, and 3D) were developed and evaluated against manually annotated reference standards. In the test dataset, mean Dice coefficients were 0.866 (2D), 0.869 (2.5D), and 0.798 (3D). Volumetric estimates showed no statistically significant differences from the reference standard, with strong correlations (Spearman's ρ = 0.976-0.988). Mean absolute errors were 0.218 (2D), 0.206 (2.5D), and 0.310 ml (3D). The 2.5D approach provided the most balanced performance between segmentation accuracy and volumetric estimation. These findings demonstrate the feasibility of automated PMCT-based segmentation and volumetric quantification of sphenoid sinus fluid, enabling quantitative assessment on PMCT images prior to autopsy.

Topics

Journal Article

Ready to Sharpen Your Edge?

Subscribe to join 11k+ peers who rely on RadAI Slice. Get the essential weekly briefing that empowers you to navigate the future of radiology.

We respect your privacy. Unsubscribe at any time.