Detection of small traumatic hemorrhages using a computer-generated average human brain CT

Liza Afzali-Hashemi* (Corresponding Author), Marieke Hazewinkel, Marleen C. Tjepkema-Cloostermans, Michel J.A.M. Van Putten, Cornelis H. Slump

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
70 Downloads (Pure)

Abstract

Computed tomography is a standard diagnostic imaging technique for patients with traumatic brain injury (TBI). A limitation is the poor-to-moderate sensitivity for small traumatic hemorrhages. A pilot study using an automatic method to detect hemorrhages <10 mm in diameter in patients with TBI is presented. We have created an average image from 30 normal noncontrast CT scans that were automatically aligned using deformable image registration as implemented in Elastix software. Subsequently, the average image was aligned to the scans of TBI patients, and the hemorrhages were detected by a voxelwise subtraction of the average image from the CT scans of nine TBI patients. An experienced neuroradiologist and a radiologist in training assessed the presence of hemorrhages in the final images and determined the false positives and false negatives. The 9 CT scans contained 67 small haemorrhages, of which 97% was correctly detected by our system. The neuroradiologist detected three false positives, and the radiologist in training found two false positives. For one patient, our method showed a hemorrhagic contusion that was originally missed. Comparing individual CT scans with a computed average may assist the physicians in detecting small traumatic hemorrhages in patients with TBI.

Original languageEnglish
Article number024004
Number of pages7
JournalJournal of medical imaging
Volume5
Issue number2
DOIs
Publication statusPublished - 21 May 2018

Keywords

  • automatic detection
  • computed tomography
  • image registration
  • traumatic brain injury

Fingerprint Dive into the research topics of 'Detection of small traumatic hemorrhages using a computer-generated average human brain CT'. Together they form a unique fingerprint.

Cite this