Multispectral segmentation
Multispectral segmentation is a method for differentiating tissue classes of similar characteristics in a single imaging modality using several independent images of the same anatomical slice in different modalities (e.g., T2, proton density, T1, etc.). This makes it easier to discriminate between different tissues, as each tissue responds differently to particular pulse sequences.
See also
Further reading
- Fletcher LM, Barsotti JB, Hornak JP (May 1993). "A multispectral analysis of brain tissues". Magn Reson Med. 29: 623–30. PMID 8505898.
{{cite journal}}: CS1 maint: multiple names: authors list (link) - Jackson EF, Narayana PA, Falconer JC (1994). "Reproducibility of nonparametric feature map segmentation for determination of normal human intracranial volumes with MR imaging data". J Magn Reson Imaging. 4: 692–700. PMID 7981514.
{{cite journal}}: CS1 maint: multiple names: authors list (link) - Vannier MW, Butterfield RL, Jordan D, Murphy WA, Levitt RG, Gado M (1985). "Multispectral analysis of magnetic resonance images". Radiology. 154: 221–224. PMID 3964938.
{{cite journal}}: CS1 maint: multiple names: authors list (link)
Content Disclaimer
Informasi ini disarikan dari Wikipedia dan disajikan kembali untuk tujuan edukasi. Konten tersedia di bawah lisensi CC BY-SA 3.0. Kami tidak bertanggung jawab atas ketidakakuratan data yang bersumber dari kontribusi publik tersebut.
- The information displayed on this website is sourced in part or in whole from Wikipedia and has been adapted for the purpose of restating it. We strive to provide accurate and relevant information, however:
- There is no guarantee of absolute accuracy. Wikipedia is an open, collaborative project that can be edited by anyone, so information is subject to change.
- It is not intended to constitute professional advice. The content displayed is for informational and educational purposes only. For important decisions (e.g., medical, legal, or financial), please consult a professional.
- Content copyright. Wikipedia is licensed under the Creative Commons Attribution-ShareAlike License (CC BY-SA). This means that content may be reused with appropriate attribution and shared under a similar license.
- Responsible use. Any risk arising from the use of information from this website is entirely the responsibility of the user.