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Updated: Mar 27, 2026

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

Shape 4.0: 3D Shape Modeling and Processing Using Semantics.

Michela Spagnuolo

IEEE Computer Graphics and Applications

|January 19, 2016

Summary

This summary is machine-generated.

Advancements in sensor, communication, and computing technologies are merging digital and physical realities. This article traces shape modeling

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Area of Science:

Computer Science
Digital Reality
Cyber-Physical Systems

Background:

Rapid advancements in sensor, communication, and computing technologies.
Emerging technologies are integrating material and digital realities, leading to cyber-physical worlds.
Current 3D modeling achieves visual realism but may not meet future communication needs.

Purpose of the Study:

To describe the evolution of shape modeling.
To outline the transition from geometry-only models to semantics-driven approaches.
To anticipate future requirements for shape modeling in cyber-physical worlds.

Main Methods:

Analysis of technological evolution trends, particularly the Web.
Historical review of shape modeling paradigms.
Conceptualization of future shape modeling frameworks.

Main Results:

Identification of distinct stages in shape modeling evolution: Shape 1.0 (geometry-only, mesh-based) to Shape 4.0 (semantics-driven).
Highlighting the limitations of current 3D modeling for future applications.
Forecasting the shift towards semantically rich shape representations.

Conclusions:

The evolution of shape modeling is driven by technological progress and the demands of cyber-physical systems.
Future shape modeling (Shape 4.0) must incorporate semantics to support advanced human communication and applications.
A paradigm shift from geometric to semantic shape representation is necessary.