- Tytuł:
- A study on spinal cord segmentation techniques
- Autorzy:
-
Jasim, M.
Brindha, T. - Powiązania:
- https://bibliotekanauki.pl/articles/1839110.pdf
- Data publikacji:
- 2018
- Wydawca:
- Polska Akademia Nauk. Instytut Badań Systemowych PAN
- Tematy:
-
segmentation
intervertebral discs (IVD)
MR image
spinal cord
Dice coefficient - Opis:
- One of the vital organs, which manage the communication between the brain and different body parts, is the spinal cord. It is highly prone to the traumatic injuries and to several diseases. The vital criteria for the clinical management are the appropriate localization and segmentation of the spinal cord. The segmentation experiences the risks, associated with the diversity in the human anatomy and contrast variation inMagnetic Resonance Imaging (MRI). Hence, an efficacious segmentation method must be devised for the effective segmentation and disc localization of the spinal cord. Correspondingly, the here contained survey provides the review of the distinct segmentation schemes for the spinal cord segmentation. At present, there is an urgent requirement for the development of an effective segmentation approach so as to outperform the existing segmentation methods. In this research article, a detailed survey on several research works presenting the recommended segmentation schemes, based on the active contour model, semi-automated segmentation, deformable model, probabilistic model, graph-based segmentation, and so on, is presented. Additionally, an in depth analysis and discussion are provided, in accordance with the publication year, evaluation metrics, segmentation scheme, Magnetic Resonance (MR) image datasets, Dice Similarity Coefficient (DSC) and accuracy. Subsequently, the research gaps and risks, related to distinct segmentation schemes are considered for directing the researchers towards a better future investigation field.
- Źródło:
-
Control and Cybernetics; 2018, 47, 4; 497-521
0324-8569 - Pojawia się w:
- Control and Cybernetics
- Dostawca treści:
- Biblioteka Nauki