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Toward automatic reformation at the orbitomeatal line in head computed tomography using object detection algorithm

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Abstract

Consistent cross-sectional imaging is desirable to accurately detect lesions and facilitate follow-up in head computed tomography (CT). However, manual reformation causes image variations among technologists and requires additional time. We therefore developed a system that reformats head CT images at the orbitomeatal (OM) line and evaluated the system performance using real-world clinical data. Retrospective data were obtained for 681 consecutive patients who underwent non-contrast head CT. The datasets were randomly divided into one of three sets for training, validation, or testing. Four landmarks (bilateral eyes and external auditory canal) were detected with the trained You Look Only Once (YOLO)v5 model, and the head CT images were reformatted at the OM line. The precision, recall, and mean average precision at the intersection over union threshold of 0.5 were computed in the validation sets. The reformation quality in testing sets was evaluated by three radiological technologists on a qualitative 4-point scale. The precision, recall, and mean average precision of the trained YOLOv5 model for all categories were 0.688, 0.949, and 0.827, respectively. In our environment, the mean implementation time was 23.5 ± 2.4 s for each case. The qualitative evaluation in the testing sets showed that post-processed images of automatic reformation had clinically useful quality with scores 3 and 4 in 86.8%, 91.2%, and 94.1% for observers 1, 2, and 3, respectively. Our system demonstrated acceptable quality in reformatting the head CT images at the OM line using an object detection algorithm and was highly time efficient.

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Acknowledgements

The authors would like to thank Enago (www.enago.jp) for the English language review.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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Authors and Affiliations

  1. Graduate School of Health Sciences, Hokkaido University, Kita-12, Nishi-5, Kita-ku, Sapporo, 060-0812, Japan

    Shota Ichikawa

  2. Department of Radiological Technology, Kurashiki Central Hospital, 1-1-1 Miwa, Kurashiki, Okayama, 710-8602, Japan

    Shota Ichikawa & Hideki Itadani

  3. Faculty of Health Sciences, Hokkaido University, Kita-12, Nishi-5, Kita-ku, Sapporo, 060-0812, Japan

    Hiroyuki Sugimori

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  1. Shota Ichikawa
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Contributions

SI contributed to the study design, data collection, algorithm construction, image evaluation, and the writing and editing of the article; HI carried out the data collection, image evaluation, and the reviewing and editing of the article; HS performed supervision, project administration, image evaluation, and reviewing and editing of the article. All authors read and approved the final manuscript.

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Correspondence to Hiroyuki Sugimori.

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The authors have no relevant financial or non-financial interests to disclose.

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This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the institutional review board of Kurashiki Central Hospital (Approval Number 3766). The requirement for individual informed consent was waived due to the retrospective nature of the study.

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Ichikawa, S., Itadani, H. & Sugimori, H. Toward automatic reformation at the orbitomeatal line in head computed tomography using object detection algorithm. Phys Eng Sci Med 45, 835–845 (2022). https://doi.org/10.1007/s13246-022-01153-z

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  • DOI: https://doi.org/10.1007/s13246-022-01153-z

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