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Pregled bibliografske jedinice broj: 10568

Radial Basis Function-based Image Segmentation using a Receptive Field


Kovačević, Domagoj; Lončarić, Sven
Radial Basis Function-based Image Segmentation using a Receptive Field // Proceedings of the Tenth Annual IEEE Symposium on Computer-Based Medical Systems / Plummer, Deborah (ur.).
Maribor, Slovenija: IEEE Computer Society, 1997. str. 126-130 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


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Naslov
Radial Basis Function-based Image Segmentation using a Receptive Field

Autori
Kovačević, Domagoj ; Lončarić, Sven

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the Tenth Annual IEEE Symposium on Computer-Based Medical Systems / Plummer, Deborah - : IEEE Computer Society, 1997, 126-130

Skup
Tenth Annual IEEE Symposium on Computer-Based Medical Systems

Mjesto i datum
Maribor, Slovenija, 11-13.06.1996

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
image processing; image analysis; image segmentation;neural networks

Sažetak
This paper presents a novel method for CT head image automatic segmentation. The images are obtained from patients having the spontaneous intra cerebral brain hemorrhage (ICH). The results of the segmentation are images partitioned into five regions of interest corresponding to four tissue classes (skull, brain, calcifications and ICH ) and background. Once the images are segmented it is possible to calculate various hemorrhage region parameters such as its size, position, etc. The segmentation is performed in three major steps. In the first phase a feature extraction and normalization is performed using a receptive field (RF). Experiments were performed to determine the optimal RF structure. Pixels are classified in the second phase using the radial basis function (RBF) artificial neural network. Experiments with different RBF network topologies were performed in order to determine the optimal basis functions, network size and a training algorithm. The segmentation results obtained using the RBF network were compared with results obtained by multi-layer perceptron neural network (MLP). In the third phase the image regions obtained by the RBF network were labeled using an expert system. Experiments have shown that the proposed method successfully performs image segmentation.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika



POVEZANOST RADA


Projekti:
036024

Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb

Profili:

Avatar Url Sven Lončarić (autor)

Avatar Url Domagoj Kovačević (autor)


Citiraj ovu publikaciju:

Kovačević, Domagoj; Lončarić, Sven
Radial Basis Function-based Image Segmentation using a Receptive Field // Proceedings of the Tenth Annual IEEE Symposium on Computer-Based Medical Systems / Plummer, Deborah (ur.).
Maribor, Slovenija: IEEE Computer Society, 1997. str. 126-130 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Kovačević, D. & Lončarić, S. (1997) Radial Basis Function-based Image Segmentation using a Receptive Field. U: Plummer, D. (ur.)Proceedings of the Tenth Annual IEEE Symposium on Computer-Based Medical Systems.
@article{article, editor = {Plummer, D.}, year = {1997}, pages = {126-130}, keywords = {image processing, image analysis, image segmentation, neural networks}, title = {Radial Basis Function-based Image Segmentation using a Receptive Field}, keyword = {image processing, image analysis, image segmentation, neural networks}, publisher = {IEEE Computer Society}, publisherplace = {Maribor, Slovenija} }
@article{article, editor = {Plummer, D.}, year = {1997}, pages = {126-130}, keywords = {image processing, image analysis, image segmentation, neural networks}, title = {Radial Basis Function-based Image Segmentation using a Receptive Field}, keyword = {image processing, image analysis, image segmentation, neural networks}, publisher = {IEEE Computer Society}, publisherplace = {Maribor, Slovenija} }




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