Computational Measuring Approach for the Identification of Probable Intestinal System Pathologies through the Human Iris Parameters

Julián D. Miranda; Sergio A. Salinas

doi:10.1109/STSIVA.2019.8730274

Computational Measuring Approach for the Identification of Probable Intestinal System Pathologies through the Human Iris Parameters

Julián D. Miranda, Sergio A. Salinas

Producción científica: Capítulo del libro/informe/acta de congreso › Ponencia publicada en las memorias del evento con ISBN › revisión exhaustiva

1 Cita (Scopus)

Resumen

Iridology is the science that aims to identify certain human pathologies through human iris by using manual visual methods. These methods, although they are less invasive, are cumbersome. In this paper, a detailed description of the results obtained by applying an algorithmic approach for the automatic identification, calculation, and computation measurements of the key internal parameters of the human eye iris and specific organic pathologies related to the intestinal system is presented. Results evidence that using composition and basic segmentation of human iris, it is possible to execute propitious computational procedures for the determination of organic anomalies in the intestinal system.

Idioma original	Inglés
Título de la publicación alojada	2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings
Editorial	Institute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)	9781728114910
DOI	https://doi.org/10.1109/STSIVA.2019.8730274
Estado	Publicada - abr. 2019
Evento	22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Bucaramanga, Colombia Duración: 24 abr. 2019 → 26 abr. 2019

Serie de la publicación

Nombre	2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings

Conferencia

Conferencia	22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019
País/Territorio	Colombia
Ciudad	Bucaramanga
Período	24/04/19 → 26/04/19

Nota bibliográfica

Publisher Copyright:
© 2019 IEEE.

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10.1109/STSIVA.2019.8730274

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Miranda, J. D., & Salinas, S. A. (2019). Computational Measuring Approach for the Identification of Probable Intestinal System Pathologies through the Human Iris Parameters. En 2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings Artículo 8730274 (2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/STSIVA.2019.8730274

Miranda, Julián D. ; Salinas, Sergio A. / Computational Measuring Approach for the Identification of Probable Intestinal System Pathologies through the Human Iris Parameters. 2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings).

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title = "Computational Measuring Approach for the Identification of Probable Intestinal System Pathologies through the Human Iris Parameters",

abstract = "Iridology is the science that aims to identify certain human pathologies through human iris by using manual visual methods. These methods, although they are less invasive, are cumbersome. In this paper, a detailed description of the results obtained by applying an algorithmic approach for the automatic identification, calculation, and computation measurements of the key internal parameters of the human eye iris and specific organic pathologies related to the intestinal system is presented. Results evidence that using composition and basic segmentation of human iris, it is possible to execute propitious computational procedures for the determination of organic anomalies in the intestinal system.",

author = "Miranda, {Juli{\'a}n D.} and Salinas, {Sergio A.}",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 ; Conference date: 24-04-2019 Through 26-04-2019",

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Miranda, JD & Salinas, SA 2019, Computational Measuring Approach for the Identification of Probable Intestinal System Pathologies through the Human Iris Parameters. En 2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings., 8730274, 2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings, Institute of Electrical and Electronics Engineers Inc., 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019, Bucaramanga, Colombia, 24/04/19. https://doi.org/10.1109/STSIVA.2019.8730274

Computational Measuring Approach for the Identification of Probable Intestinal System Pathologies through the Human Iris Parameters. / Miranda, Julián D.; Salinas, Sergio A.
2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. 8730274 (2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings).

Producción científica: Capítulo del libro/informe/acta de congreso › Ponencia publicada en las memorias del evento con ISBN › revisión exhaustiva

TY - GEN

T1 - Computational Measuring Approach for the Identification of Probable Intestinal System Pathologies through the Human Iris Parameters

AU - Miranda, Julián D.

AU - Salinas, Sergio A.

PY - 2019/4

Y1 - 2019/4

N2 - Iridology is the science that aims to identify certain human pathologies through human iris by using manual visual methods. These methods, although they are less invasive, are cumbersome. In this paper, a detailed description of the results obtained by applying an algorithmic approach for the automatic identification, calculation, and computation measurements of the key internal parameters of the human eye iris and specific organic pathologies related to the intestinal system is presented. Results evidence that using composition and basic segmentation of human iris, it is possible to execute propitious computational procedures for the determination of organic anomalies in the intestinal system.

AB - Iridology is the science that aims to identify certain human pathologies through human iris by using manual visual methods. These methods, although they are less invasive, are cumbersome. In this paper, a detailed description of the results obtained by applying an algorithmic approach for the automatic identification, calculation, and computation measurements of the key internal parameters of the human eye iris and specific organic pathologies related to the intestinal system is presented. Results evidence that using composition and basic segmentation of human iris, it is possible to execute propitious computational procedures for the determination of organic anomalies in the intestinal system.

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U2 - 10.1109/STSIVA.2019.8730274

DO - 10.1109/STSIVA.2019.8730274

M3 - Ponencia publicada en las memorias del evento con ISBN

AN - SCOPUS:85068084229

T3 - 2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings

BT - 2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019

Y2 - 24 April 2019 through 26 April 2019

ER -

Miranda JD, Salinas SA. Computational Measuring Approach for the Identification of Probable Intestinal System Pathologies through the Human Iris Parameters. En 2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. 8730274. (2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings). doi: 10.1109/STSIVA.2019.8730274

Computational Measuring Approach for the Identification of Probable Intestinal System Pathologies through the Human Iris Parameters

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