2017
DOI: 10.1007/s11548-016-1516-y
|View full text |Cite
|
Sign up to set email alerts
|

Automatic detection of vertebral number abnormalities in body CT images

Abstract: Our algorithm successfully determined the number of vertebrae, and the feasibility of our proposed system was validated.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2019
2019
2024
2024

Publication Types

Select...
3
2

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(1 citation statement)
references
References 30 publications
0
1
0
Order By: Relevance
“…In the case of L6, which itself acts as a strong prior due to the sacrum, its reliable detection doesn't seem as consistent. Hanaoka et al (2017) , for example, recognise this issue and work towards directly predicting such abnormal numbers. Nonetheless, the improved behaviour of the approaches in such anatomical variations brings us closer to realising automated algorithms in clinical settings.…”
Section: On Rare Anatomical Variations: Transitional Vertebraementioning
confidence: 99%
“…In the case of L6, which itself acts as a strong prior due to the sacrum, its reliable detection doesn't seem as consistent. Hanaoka et al (2017) , for example, recognise this issue and work towards directly predicting such abnormal numbers. Nonetheless, the improved behaviour of the approaches in such anatomical variations brings us closer to realising automated algorithms in clinical settings.…”
Section: On Rare Anatomical Variations: Transitional Vertebraementioning
confidence: 99%