DC Field | Value | Language |
dc.contributor.author | AVILA MORA, IVONNE MARICELA | - |
dc.contributor.author | MENDOZA CHAPA, SONIA GUADALUPE | - |
dc.contributor.author | GARCIA GARCIA, ELVIA KIMBERLY | - |
dc.contributor.author | DECOUCHANT, DOMINIQUE EMILE HENRI | - |
dc.contributor.author | PUENTE MAURY, LILIANA | - |
dc.contributor.author | DELGADO HERNANDEZ, ROSA DELIA | - |
dc.contributor.author | MARRUFO MELENDEZ, OSCAR | - |
dc.contributor.author | SAN JUAN ORTA, DANIEL | - |
dc.coverage.spatial | <dc:creator id="info:eu-repo/dai/mx/cvu/207776">IVONNE MARICELA AVILA MORA</dc:creator> | - |
dc.coverage.spatial | <dc:creator id="info:eu-repo/dai/mx/cvu/36074">SONIA GUADALUPE MENDOZA CHAPA</dc:creator> | - |
dc.coverage.spatial | <dc:creator id="info:eu-repo/dai/mx/cvu/206169">ELVIA KIMBERLY GARCIA GARCIA</dc:creator> | - |
dc.coverage.spatial | <dc:creator id="info:eu-repo/dai/mx/cvu/214649">DOMINIQUE EMILE HENRI DECOUCHANT</dc:creator> | - |
dc.coverage.spatial | <dc:creator id="info:eu-repo/dai/mx/cvu/269532">LILIANA PUENTE MAURY</dc:creator> | - |
dc.coverage.spatial | <dc:creator id="info:eu-repo/dai/mx/cvu/41964">OSCAR MARRUFO MELENDEZ</dc:creator> | - |
dc.coverage.spatial | <dc:creator id="info:eu-repo/dai/mx/cvu/309200">DANIEL SAN JUAN ORTA</dc:creator> | - |
dc.coverage.temporal | <dc:subject>info:eu-repo/classification/cti/3</dc:subject> | - |
dc.date.accessioned | 2021-04-07T21:44:17Z | - |
dc.date.available | 2021-04-07T21:44:17Z | - |
dc.date.issued | 2013 | - |
dc.identifier.citation | Research in Computing Science 68 (2013) | en_US |
dc.identifier.uri | http://ilitia.cua.uam.mx:8080/jspui/handle/123456789/650 | - |
dc.description.abstract | The detection of scars in the cerebral cortex usually involves a manual process performed by radiologists, who have to face multiple troubles. For example, the bad calibration of the equipment used to get
images of the cerebral cortex can cause spacial and geometrical distortions in the MRI (Magnetic Resonance Imaging) sequences. Owing to the
advances in algorithms capable of analyzing MRI sequences, it is possible
to automatically detect scars in the cerebral cortex in a successful way. In
addition, an automatic process for finding scars can decrease the subjec tivity of human interpretations and serve as a tool to support diagnoses
of diseases. In this paper, we propose a new methodology to detect scars
in the cerebral cortex by means of the analysis of intensities in T2/MRI
sequences. In particular, we implement three main algorithms: the region
growing, thresholds, and artificial neural networks. | en_US |
dc.description.sponsorship | Instituto Politécnico Nacional, Centro de Investigación en Computación | en_US |
dc.language.iso | Inglés | en_US |
dc.publisher | México : Instituto Politécnico Nacional, Centro de Investigación en Computación | en_US |
dc.relation.haspart | 1870-4069 | - |
dc.rights | https://www.rcs.cic.ipn.mx/2013_68/Characterizing%20Scars%20in%20the%20Cerebral%20Cortex%20by%20Analyzing%20Intensities%20in%20T2nMRI%20Sequences.pdf | - |
dc.subject | Corteza cerebral - Fisiología | en_US |
dc.subject | Cerebro - Resonancia magnética en imágenes | en_US |
dc.title | Characterizing scars in the cerebral cortex by analyzing intensities in T2/MRI sequences | en_US |
dc.type | Artículo | en_US |
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