Development of Semi-automated Segmentation of the Brain and CSF Region on MR Images

Hayashi, Norio; Sakuta, Keita; Sanada, Shigeru; Suzuki, Masayuki; Matsuura, Yukihiro; Yamamoto, Tomoko; Matsui, Osamu

doi:10.6009/jjrt.64.1352

Cited by 2 publications

(1 citation statement)

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“…The brain and cerebrospinal-fluid (CSF) regions were segmented using a semiautomated segmentation method on MR images obtained with SE and GRE sequences [19]. A flow chart of the segmentation method of the brain region is shown in Fig.…”

Section: Segmentation Of Brain and Cerebrospinal-fluid Regionsmentioning

confidence: 99%

Development of identification of the central sulcus in brain magnetic resonance imaging

Hayashi

Sakuta

Minehiro

et al. 2010

Radiol Phys Technol

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Magnetic resonance imaging (MRI) is useful in the quantitative evaluation of brain atrophy, because the superior contrast resolution facilitates separation of the gray and white matter. Quantitative assessment of brain atrophy has mainly been performed by manual measurement, which requires considerable time and effort to determine the brain volume. Therefore, computer-aided quantitative measurement methods for the diagnosis of brain atrophy are required. We have developed a method of segmenting the cerebrum, cerebellum-brainstem, and temporal lobe simultaneously on MR images obtained in a single sequence. It is important to measure the volume of not only these regions but also the frontal lobe in clinical use. However, for segmenting the frontal lobe, it is necessary to identify the Sylvian fissure and the central sulcus, which represent boundaries. Here, we developed a method of identifying the central sulcus from MR images obtained with a 1.5 T MRI scanner. The brain and the cerebrospinal fluid (CSF) regions were segmented using semiautomated segmentation method on MR images. The central sulcus shows an oblique line from the inside to the outside on the convexity view. The almost straight appearance of the central sulcus was used for segmentation of the central sulcus from the segmented CSF images. The central sulcus was identified with this technique in 77% of the images obtained by all sequences. This technique for identifying the central sulcus is very important not only for volumetry, but also for clinical diagnosis.

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Section: Segmentation Of Brain and Cerebrospinal-fluid Regionsmentioning

confidence: 99%