dc.contributor.author |
Thireou, T |
en |
dc.contributor.author |
Kontaxakis, G |
en |
dc.contributor.author |
Strauss, LG |
en |
dc.contributor.author |
Dimitrakopoulou-Strauss, A |
en |
dc.contributor.author |
Pavlopoulos, S |
en |
dc.contributor.author |
Santos, A |
en |
dc.date.accessioned |
2014-03-01T01:22:23Z |
|
dc.date.available |
2014-03-01T01:22:23Z |
|
dc.date.issued |
2005 |
en |
dc.identifier.issn |
0140-0118 |
en |
dc.identifier.uri |
https://dspace.lib.ntua.gr/xmlui/handle/123456789/16549 |
|
dc.subject |
Dynamic PET |
en |
dc.subject |
Feature extraction |
en |
dc.subject |
Positron emission tomography |
en |
dc.subject |
Similarity mapping |
en |
dc.subject |
Standardized uptake value |
en |
dc.subject.classification |
Computer Science, Interdisciplinary Applications |
en |
dc.subject.classification |
Engineering, Biomedical |
en |
dc.subject.classification |
Mathematical & Computational Biology |
en |
dc.subject.classification |
Medical Informatics |
en |
dc.subject.other |
Cells |
en |
dc.subject.other |
Computer simulation |
en |
dc.subject.other |
Diagnosis |
en |
dc.subject.other |
Imaging techniques |
en |
dc.subject.other |
Maps |
en |
dc.subject.other |
Positron emission tomography |
en |
dc.subject.other |
Tumors |
en |
dc.subject.other |
Correlation coefficients (COR) |
en |
dc.subject.other |
Lesions |
en |
dc.subject.other |
Normalization correlation coefficients (NCOR) |
en |
dc.subject.other |
Similarity mapping (SM) |
en |
dc.subject.other |
Oncology |
en |
dc.subject.other |
fluorodeoxyglucose f 18 |
en |
dc.subject.other |
article |
en |
dc.subject.other |
calculation |
en |
dc.subject.other |
cancer diagnosis |
en |
dc.subject.other |
cancer localization |
en |
dc.subject.other |
cancer recurrence |
en |
dc.subject.other |
clinical article |
en |
dc.subject.other |
colorectal cancer |
en |
dc.subject.other |
controlled study |
en |
dc.subject.other |
correlation coefficient |
en |
dc.subject.other |
diagnostic procedure |
en |
dc.subject.other |
feasibility study |
en |
dc.subject.other |
giant cell tumor |
en |
dc.subject.other |
human |
en |
dc.subject.other |
human tissue |
en |
dc.subject.other |
image analysis |
en |
dc.subject.other |
positron emission tomography |
en |
dc.subject.other |
reference value |
en |
dc.subject.other |
simulation |
en |
dc.subject.other |
standardization |
en |
dc.subject.other |
Colorectal Neoplasms |
en |
dc.subject.other |
Feasibility Studies |
en |
dc.subject.other |
Fluorodeoxyglucose F18 |
en |
dc.subject.other |
Humans |
en |
dc.subject.other |
Image Processing, Computer-Assisted |
en |
dc.subject.other |
Neoplasm Recurrence, Local |
en |
dc.subject.other |
Neoplasms |
en |
dc.subject.other |
Phantoms, Imaging |
en |
dc.subject.other |
Positron-Emission Tomography |
en |
dc.subject.other |
Radiopharmaceuticals |
en |
dc.title |
Feasibility study of the use of similarity maps in the evaluation of oncological dynamic positron emission tomography images |
en |
heal.type |
journalArticle |
en |
heal.identifier.primary |
10.1007/BF02345119 |
en |
heal.identifier.secondary |
http://dx.doi.org/10.1007/BF02345119 |
en |
heal.language |
English |
en |
heal.publicationDate |
2005 |
en |
heal.abstract |
A preliminary study is presented on the potential role of similarity mapping (SM) in the evaluation of oncological dynamic 18F-fluorodeoxyglucose positron emission tomography studies, mainly in lesion localisation and detectability. Similarity maps were calculated using previously described (correlation coefficient (COR) and normalised correlation coefficient (NCOR)) and newly introduced similarity measures (sum of squares coefficient (SSQ), squared sum coefficient (SQS), sum of cubes coefficient (SC) and cubed sum coefficient (CS)). The results were evaluated using simulated and clinical data. The study revealed that the best-suited similarity measure for such applications was the CS similarity coefficient, which provided the best parametric images, delineating structures of interest and supporting the visual interpretation of data sets. It was shown that SM and standardised uptake value (SUV) images had comparable diagnostic performance, although SM was able to offer additional time-related information in a single image. For the case of colorectal recurrences (17 cases), the measured contrast values for the CS and SUV images were 2.36 ± 0.47 and 4.12 ± 0.42, respectively, whereas, for three cases of giant cell tumours, these values were 11.6 ± 2.1 and 11.9 ± 1.8, respectively. © IFMBE: 2005. |
en |
heal.publisher |
PETER PEREGRINUS LTD |
en |
heal.journalName |
Medical and Biological Engineering and Computing |
en |
dc.identifier.doi |
10.1007/BF02345119 |
en |
dc.identifier.isi |
ISI:000226938000005 |
en |
dc.identifier.volume |
43 |
en |
dc.identifier.issue |
1 |
en |
dc.identifier.spage |
23 |
en |
dc.identifier.epage |
32 |
en |