"7330" Dotaz Zobrazit nápovědu
elektronický časopis
- Konspekt
- Psychiatrie
- NLK Obory
- psychiatrie
- NLK Publikační typ
- elektronické časopisy
A cross-sectional study explored the moral judgement competence and moral attitudes of 310 Czech and Slovak and 70 foreign national students at the Medical Faculty of Charles University in Hradec Králové, Czech Republic. Lind's Moral Judgement Test was used to evaluate moral judgement competence and moral attitudes depending on factors such as age, number of semesters of study, sex, nationality and religion. Moral judgement competence decreased significantly in the Czech and Slovak medical students as they grew older; in medical students from other countries it did not significantly increase. The influence of other factors (sex, nationality and religion) on moral judgement competence was not proven in either the Czech and Slovak or the foreign national medical students. Moral attitudes do not change; the Czech and Slovak as well as the foreign students preferred the post-conventional levels of moral judgement (Kohlberg's 5th and 6th stages). The fact that the Czech and Slovak students' moral judgement competence decreased with age and number of semesters of study completed is not an optimistic sign: medical students who had undergone a lower number of semesters of study were morally more competent.
- MeSH
- charakteristiky bydlení MeSH
- dospělí MeSH
- lékařská etika výchova MeSH
- lidé MeSH
- mínění etika MeSH
- mladiství MeSH
- mravy MeSH
- multivariační analýza MeSH
- odborná způsobilost normy MeSH
- ošetřovatelská metodologie - výzkum MeSH
- postoj zdravotnického personálu etnologie MeSH
- průřezové studie MeSH
- průzkumy a dotazníky MeSH
- regresní analýza MeSH
- studenti lékařství psychologie statistika a číselné údaje MeSH
- studium lékařství pregraduální MeSH
- věkové faktory MeSH
- zahraniční odborný personál statistika a číselné údaje MeSH
- zdraví - znalosti, postoje, praxe MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mladiství MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- srovnávací studie MeSH
- Geografické názvy
- Česká republika MeSH
- Slovenská republika MeSH
BACKGROUND: Segmentation of pre-operative low-grade gliomas (LGGs) from magnetic resonance imaging is a crucial step for studying imaging biomarkers. However, segmentation of LGGs is particularly challenging because they rarely enhance after gadolinium administration. Like other gliomas, they have irregular tumor shape, heterogeneous composition, ill-defined tumor boundaries, and limited number of image types. To overcome these challenges we propose a semi-automated segmentation method that relies only on T2-weighted (T2W) and optionally post-contrast T1-weighted (T1W) images. METHODS: First, the user draws a region-of-interest (ROI) that completely encloses the tumor and some normal tissue. Second, a normal brain atlas and post-contrast T1W images are registered to T2W images. Third, the posterior probability of each pixel/voxel belonging to normal and abnormal tissues is calculated based on information derived from the atlas and ROI. Finally, geodesic active contours use the probability map of the tumor to shrink the ROI until optimal tumor boundaries are found. This method was validated against the true segmentation (TS) of 30 LGG patients for both 2D (1 slice) and 3D. The TS was obtained from manual segmentations of three experts using the Simultaneous Truth and Performance Level Estimation (STAPLE) software. Dice and Jaccard indices and other descriptive statistics were computed for the proposed method, as well as the experts' segmentation versus the TS. We also tested the method with the BraTS datasets, which supply expert segmentations. RESULTS AND DISCUSSION: For 2D segmentation vs. TS, the mean Dice index was 0.90 ± 0.06 (standard deviation), sensitivity was 0.92, and specificity was 0.99. For 3D segmentation vs. TS, the mean Dice index was 0.89 ± 0.06, sensitivity was 0.91, and specificity was 0.99. The automated results are comparable with the experts' manual segmentation results. CONCLUSIONS: We present an accurate, robust, efficient, and reproducible segmentation method for pre-operative LGGs.
- MeSH
- algoritmy MeSH
- gliom patologie chirurgie MeSH
- lidé MeSH
- magnetická rezonanční tomografie * metody MeSH
- nádory mozku patologie chirurgie MeSH
- počítačové zpracování obrazu * MeSH
- senzitivita a specificita MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
