Discrimination of intracerebral hematoma and intraventricular hemorrhage in initial CT images using hierarchical region extraction method

Kazunori Oka; Daisuke Fujita; Koichi Arimura; Koji Iihara; Syoji Kobashi

doi:10.1117/12.2667011

25 March 2023 Discrimination of intracerebral hematoma and intraventricular hemorrhage in initial CT images using hierarchical region extraction method

Kazunori Oka, Daisuke Fujita, Koichi Arimura, Koji Iihara, Syoji Kobashi

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Proceedings Volume 12592, International Workshop on Advanced Imaging Technology (IWAIT) 2023; 125922M (2023) https://doi.org/10.1117/12.2667011
Event: International Workshop on Advanced Imaging Technology (IWAIT) 2023, 2023, Jeju, Korea, Republic of

Abstract

Intracerebral hematoma (ICH) is a blood clot that forms when a blood vessel in the brain ruptures for some reason and the spilled blood coagulates. ICH has a high morbidity and mortality rate, accounting for approximately 10% of all strokes. Manual segmentation of ICH in head CT images is very complicated, time consuming, and troublesome. When ICH perforates the ventricular wall and blood flows into the ventricle, there is little difference in CT value between ICH and intraventricular hemorrhage (IVH), and the boundary between them is unclear. Convolutional neural network (CNN) has proven to be a reliable method in the field of image recognition. In addition, quantification of ICH may aid in decision making in ICH treatment. In this study, we introduce CNN in a stepwise manner to differentiate ICH and IVH in the process and extract ICH regions. The results in 18 stroke patients show that our method is promising in the extraction of ICH regions with an accuracy of 75.2%.

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Kazunori Oka, Daisuke Fujita, Koichi Arimura, Koji Iihara, and Syoji Kobashi "Discrimination of intracerebral hematoma and intraventricular hemorrhage in initial CT images using hierarchical region extraction method", Proc. SPIE 12592, International Workshop on Advanced Imaging Technology (IWAIT) 2023, 125922M (25 March 2023); https://doi.org/10.1117/12.2667011

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KEYWORDS

Image segmentation

Brain

Computed tomography

X-ray computed tomography

Blood

Head

Absorption

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