Robust modelling of local image structures and its application to medical imagery
UNSPECIFIED (2004) Robust modelling of local image structures and its application to medical imagery. In: 17th International Conference on Pattern Recognition (ICPR), British Machine Vis Assoc, Cambridge, ENGLAND, AUG 23-26, 2004. Published in: PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 3 pp. 534-537.Full text not available from this repository.
A robust modelling method for detecting and measuring isotropic, linear features and bifurcations is described and applied to analysing 2d eletrophoresis and retinal images. Features are modelled as a superposition of Gaussian functions with the Hermite expansion and estimated by a combination of a multiresolution, windowed Fourier approach followed by an EM type of spatial regression. A penalised likelihood test, the Akakie Information criteria (AIC) is used to select the best model and scale for feature segments. Results are shown by using samples on both gel and retinal images.
|Item Type:||Conference Item (UNSPECIFIED)|
|Subjects:||Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software|
|Series Name:||INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION|
|Journal or Publication Title:||PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 3|
|Publisher:||IEEE COMPUTER SOC|
|Editor:||Kittler, J and Petrou, M and Nixon, M|
|Number of Pages:||4|
|Page Range:||pp. 534-537|
|Title of Event:||17th International Conference on Pattern Recognition (ICPR)|
|Location of Event:||British Machine Vis Assoc, Cambridge, ENGLAND|
|Date(s) of Event:||AUG 23-26, 2004|
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