Journal of
Systemics, Cybernetics and Informatics
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ISSN: 1690-4524 (Online)


Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.

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Published by
The International Institute of Informatics and Cybernetics


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Academia.edu
(A Community of about 40.000.000 Academics)


Honorary Editorial Advisory Board's Chair
William Lesso (1931-2015)

Editor-in-Chief
Nagib C. Callaos


Sponsored by
The International Institute of
Informatics and Systemics

www.iiis.org
 

Editorial Advisory Board

Quality Assurance

Editors

Journal's Reviewers
Call for Special Articles
 

Description and Aims

Submission of Articles

Areas and Subareas

Information to Contributors

Editorial Peer Review Methodology

Integrating Reviewing Processes


Utilization of Artificial Intelligence by Students in Interdisciplinary Field of Biomedical Engineering
Shigehiro Hashimoto
(pages: 1-5)

Transdisciplinary Applications of Data Visualization and Data Mining Techniques as Represented for Human Diseases
Richard S. Segall
(pages: 6-15)

Beyond Status Quo: Why is Transdisciplinary Communication Instrumental in Innovation?
James Lipuma, Cristo Leon
(pages: 16-20)

How We Can Locate Validatable Foundations of Life Themes
Jeremy Horne
(pages: 21-32)

Bringing Discipline into Transdisciplinary Communications -The ISO 56000 Family of Innovation Standards-
Rick Fernandez, William Swart
(pages: 33-39)

To AI Is Human: How AI Tools with Their Imperfections Enhance Learning
Martin Cwiakala
(pages: 40-46)

Knowledge, Learning and Transdisciplinary Communication in the Evolution of the Contemporary World
Rita Micarelli, Giorgio Pizziolo
(pages: 47-52)

Human Complexity vs. Machine Linearity: Tug-of-War Between Two Realities Coexisting in Precarious Balance
Paolo Barile, Clara Bassano, Paolo Piciocchi
(pages: 53-62)

A Cybernetic Metric Approach to Course Preparation
Russell Jay Hendel
(pages: 63-70)

The Impact of Artificial Intelligence on Education
John Jenq
(pages: 71-76)

Bridging the Gap: Harnessing the Power of Machine Learning and Big Data for Media Research
Li-jing Arthur Chang
(pages: 77-84)

Image Processing, Computer Vision, Data Visualization, and Data Mining for Transdisciplinary Visual Communication: What Are the Differences and Which Should or Could You Use?
Richard S. Segall
(pages: 85-92)

Identification – The Essence of Education
Jeremy Horne
(pages: 93-99)

The Greek-Roman Theatre in the Mediterranean Area
Maria Rosaria D’acierno Canonici Cammino
(pages: 100-108)

Examination of AI and Conventional Teaching Approaches in Cultivating Critical Thinking Skills in High School Students
Luis Castillo
(pages: 109-112)

Thoughts, Labyrinths, and Torii
Maurício Vieira Kritz
(pages: 113-119)

Can Two Human Intelligences (HIs or Noes) and Two Artificial Intelligences (AIs) Get Involved in Interlinguistic Communication? – A Transdisciplinary Quest
Ekaterini Nikolarea
(pages: 120-128)


 

Abstracts

 


ABSTRACT


3D Interpolation Method for CT Images of the Lung

Noriaki Asada, Mayumi Ogura


A 3-D image can be reconstructed from numerous CT images of the lung. The procedure reconstructs a solid from multiple cross section images, which are collected during pulsation of the heart. Thus the motion of the heart is a special factor that must be taken into consideration during reconstruction. The lung exhibits a repeating transformation synchronized to the beating of the heart as an elastic body. There are discontinuities among neighboring CT images due to the beating of the heart, if no special techniques are used in taking CT images. The 3-D heart image is reconstructed from numerous CT images in which both the heart and the lung are taken. Although the outline shape of the reconstructed 3-D heart is quite unnatural, the envelope of the 3-D unnatural heart is fit to the shape of the standard heart. The envelopes of the lung in the CT images are calculated after the section images of the best fitting standard heart are located at the same positions of the CT images. Thus the CT images are geometrically transformed to the optimal CT images fitting best to the standard heart. Since correct transformation of images is required, an Area oriented interpolation method proposed by us is used for interpolation of transformed images. An attempt to reconstruct a 3-D lung image by a series of such operations without discontinuity is shown. Additionally, the same geometrical transformation method to the original projection images is proposed as a more advanced method.

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