The primary purpose of digital nuclear magnetic resonance encephalic image analysis is highlighting, on the original picture generated by the NMR device, the basic components of the image itself: Eventual Cerebral Anomaly, Cerebral Tissue, Rest of the Image, Background. These items are identified as "different objects" of the same original image. This "differentiation" inside the original image is extremely important because it is the first step to make before dealing with a multitude of critical tasks such as: diagnosis, analysis, peculiar zone delineation, abnormal masses identification and irradiation, three-dimensional internal organ reconstruction, tissue characterization and so on. The object of the present work is the creation of a "Univocal Numerical Characterization" of the above mentioned four basic components, in order to make a "Classification" of each set pixels inside each original image.

Encephalic NMR Image Classification / Avola, Danilo. - (2005), pp. 124-128. (Intervento presentato al convegno 3rd International Conference on Computer Science and its Applications (ICCSA-2005) tenutosi a National University, 9388 Lightwave Avenue , San Diego , California, 92123, U.S.A.).

Encephalic NMR Image Classification

Danilo Avola
2005

Abstract

The primary purpose of digital nuclear magnetic resonance encephalic image analysis is highlighting, on the original picture generated by the NMR device, the basic components of the image itself: Eventual Cerebral Anomaly, Cerebral Tissue, Rest of the Image, Background. These items are identified as "different objects" of the same original image. This "differentiation" inside the original image is extremely important because it is the first step to make before dealing with a multitude of critical tasks such as: diagnosis, analysis, peculiar zone delineation, abnormal masses identification and irradiation, three-dimensional internal organ reconstruction, tissue characterization and so on. The object of the present work is the creation of a "Univocal Numerical Characterization" of the above mentioned four basic components, in order to make a "Classification" of each set pixels inside each original image.
2005
3rd International Conference on Computer Science and its Applications (ICCSA-2005)
classification; image analysis; texture analysis; medical image; co-occurrence matrix
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Encephalic NMR Image Classification / Avola, Danilo. - (2005), pp. 124-128. (Intervento presentato al convegno 3rd International Conference on Computer Science and its Applications (ICCSA-2005) tenutosi a National University, 9388 Lightwave Avenue , San Diego , California, 92123, U.S.A.).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1248163
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