| 000 | 03055nam a22005775i 4500 | ||
|---|---|---|---|
| 001 | 978-1-4614-1909-9 | ||
| 003 | DE-He213 | ||
| 005 | 20140220083244.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 111214s2012 xxu| s |||| 0|eng d | ||
| 020 |
_a9781461419099 _9978-1-4614-1909-9 |
||
| 024 | 7 |
_a10.1007/978-1-4614-1909-9 _2doi |
|
| 050 | 4 | _aTK5102.9 | |
| 050 | 4 | _aTA1637-1638 | |
| 050 | 4 | _aTK7882.S65 | |
| 072 | 7 |
_aTTBM _2bicssc |
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_aUYS _2bicssc |
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_aTEC008000 _2bisacsh |
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| 072 | 7 |
_aCOM073000 _2bisacsh |
|
| 082 | 0 | 4 |
_a621.382 _223 |
| 100 | 1 |
_aStanescu, Liana. _eauthor. |
|
| 245 | 1 | 0 |
_aCreating New Medical Ontologies for Image Annotation _h[electronic resource] : _bA Case Study / _cby Liana Stanescu, Dumitru Dan Burdescu, Marius Brezovan, Cristian Gabriel Mihai. |
| 264 | 1 |
_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2012. |
|
| 300 |
_aVIII, 111p. 27 illus., 10 illus. in color. _bonline resource. |
||
| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
||
| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
||
| 490 | 1 |
_aSpringerBriefs in Electrical and Computer Engineering, _x2191-8112 |
|
| 505 | 0 | _aContent Based Image Retrieval in Medical Images Databases -- Medical Images Segmentation -- Ontologies -- Medical Images Annotation -- Semantic Based Image Retrieval -- Object Oriented Medical Annotation System. | |
| 520 | _aCreating New Medical Ontologies for Image Annotation focuses on the problem of the medical images automatic annotation process, which is solved in an original manner by the authors. All the steps of this process are described in detail with algorithms, experiments and results. The original algorithms proposed by authors are compared with other efficient similar algorithms. In addition, the authors treat the problem of creating ontologies in an automatic way, starting from Medical Subject Headings (MESH). They have presented some efficient and relevant annotation models and also the basics of the annotation model used by the proposed system: Cross Media Relevance Models. Based on a text query the system will retrieve the images that contain objects described by the keywords. | ||
| 650 | 0 | _aEngineering. | |
| 650 | 0 | _aRadiology, Medical. | |
| 650 | 0 | _aComputer software. | |
| 650 | 0 | _aComputer vision. | |
| 650 | 1 | 4 | _aEngineering. |
| 650 | 2 | 4 | _aSignal, Image and Speech Processing. |
| 650 | 2 | 4 | _aImaging / Radiology. |
| 650 | 2 | 4 | _aImage Processing and Computer Vision. |
| 650 | 2 | 4 | _aAlgorithm Analysis and Problem Complexity. |
| 700 | 1 |
_aBurdescu, Dumitru Dan. _eauthor. |
|
| 700 | 1 |
_aBrezovan, Marius. _eauthor. |
|
| 700 | 1 |
_aMihai, Cristian Gabriel. _eauthor. |
|
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer eBooks | |
| 776 | 0 | 8 |
_iPrinted edition: _z9781461419082 |
| 830 | 0 |
_aSpringerBriefs in Electrical and Computer Engineering, _x2191-8112 |
|
| 856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-1-4614-1909-9 |
| 912 | _aZDB-2-ENG | ||
| 999 |
_c101158 _d101158 |
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