The Statistical Evaluation of Data Obtained via the Manual Segmentation of MRI images of a Pathological Tissue
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F14%3APU110554" target="_blank" >RIV/00216305:26220/14:PU110554 - isvavai.cz</a>
Alternative codes found
RIV/68081731:_____/14:00433089
Result on the web
<a href="http://piers.org/piersproceedings/download.php?file=cGllcnMyMDE0R3Vhbmd6aG91fDNQMF8xODk4LnBkZnwxNDAzMjAwNDUyNTQ=" target="_blank" >http://piers.org/piersproceedings/download.php?file=cGllcnMyMDE0R3Vhbmd6aG91fDNQMF8xODk4LnBkZnwxNDAzMjAwNDUyNTQ=</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
The Statistical Evaluation of Data Obtained via the Manual Segmentation of MRI images of a Pathological Tissue
Original language description
The authors present a statistical evaluation of the MRI images of bones and soft tissues. MRI imaging of small bones is a problem issue because the measured bone images are loaded with susceptibility artifacts and low signal-to-noise ratio. Therefore, we compare the commonly used MRI contrast and looking for the best contrast to bone marrow imaging. The acquired images are classified in terms of the signal-to-noise ratio, intensity difference and steepness of the edges. The aim of this research was to statistically evaluate and determine the deviation of MRI images; this step was performed by several experts. These specialists conducted proper segmenting of pathological and healthy tissues, and they also compared the selected areas. In some cases, especially when the boundaries of the area are not clearly visible, the problem is to delimit the bone marrow area. Therefore, it is not possible to use automatic segmentation algorithms, and we focused on the manual evaluation of the statistical data in the area of the patient's bone marrow pathology (e.g. the probability of cyst formation can be determined from abnormal levels of vitamin D and osteocalcin).
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20201 - Electrical and electronic engineering
Result continuities
Project
<a href="/en/project/GAP102%2F12%2F1104" target="_blank" >GAP102/12/1104: Study of metabolism and localization of high grade glioma using MR imaging techniques</a><br>
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
PIERS 2014 Guangzhou Proceedings
ISBN
978-1-934142-28-8
ISSN
1559-9450
e-ISSN
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Number of pages
4
Pages from-to
1898-1901
Publisher name
Neuveden
Place of publication
Guangzhou, China
Event location
Guangzhou
Event date
Aug 25, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000393225900421