Multi-agent Approach for Image Processing: A Case Study for MRI Human Brain Scans Interpretation

2003 ◽  
pp. 91-100 ◽  
Author(s):  
Nathalie Richard ◽  
Michel Dojat ◽  
Catherine Garbay
Keyword(s):  
Image Processing ◽  
Human Brain ◽  
Brain Scans ◽  
Multi Agent

scholarly journals Deep learning of quality control for stereotaxic registration of human brain MRI

2018 ◽  
Author(s):  
Vladimir S. Fonov ◽  
Mahsa Dadar ◽  
D. Louis Collins ◽  
Keyword(s):  
Image Processing ◽  
Quality Control ◽  
Deep Learning ◽  
Human Brain ◽  
Control Method ◽  
False Positive Rate ◽  
Brain Mri ◽  
Brain Scans ◽  
Positive Rate ◽  
Mri Scans

AbstractLinear registration to stereotaxic space is a common first step in many automated image-processing tools for analysis of human brain MRI scans. This step is crucial for the success of the following image-processing steps. Several well-established algorithms are commonly used in the field of neuroimaging for this task, but none of them has a 100% success rate. Manual assessment of the registration is commonly used as part of quality control.We propose a completely automatic quality control method based on deep learning that replaces human rater and accurately performs quality control assessment for stereotaxic registration of T1w brain scans.In a recently published study from our group comparing linear registration methods, we used a database of 9693 MRI scans from several publically available datasets and applied five linear registration tools. In this study, the resulting images that were assessed and labeled by a human rater are used to train a deep neural network to detect cases when registration failed.Our method was able to achieve 88% accuracy and 11% false positive rate in detecting scans that should pass quality control, better than a manual QC rater.

Art and the Brain’s Reward System

2018 ◽  
Author(s):  
Henrik Hogh-Olesen
Keyword(s):  
Human Brain ◽  
Reward System ◽  
Human Existence ◽  
Brain Scans ◽  
System P ◽  
The Aesthetic ◽  
The Brain ◽  
Reward Circuit

Chapter 7 takes the investigation of the aesthetic impulse into the human brain to understand, first, why only we—and not our closest relatives among the primates—express ourselves aesthetically; and second, how the brain reacts when presented with aesthetic material. Brain scans are less useful when you are interested in the Why of aesthetic behavior rather than the How. Nevertheless, some brain studies have been ground-breaking, and neuroaesthetics offers a pivotal argument for the key function of the aesthetic impulse in human lives; it shows us that the brain’s reward circuit is activated when we are presented with aesthetic objects and stimuli. For why reward a perception or an activity that is evolutionarily useless and worthless in relation to human existence?

scholarly journals A Programming Approach to Collective Autonomy

2021 ◽  
Vol 10 (2) ◽  
pp. 27
Author(s):  
Roberto Casadei ◽  
Gianluca Aguzzi ◽  
Mirko Viroli
Keyword(s):  
Autonomous Vehicles ◽  
Autonomic Computing ◽  
Autonomous Agents ◽  
Programming Approach ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent ◽  
Simulated Case ◽  
Complex Settings

Research and technology developments on autonomous agents and autonomic computing promote a vision of artificial systems that are able to resiliently manage themselves and autonomously deal with issues at runtime in dynamic environments. Indeed, autonomy can be leveraged to unburden humans from mundane tasks (cf. driving and autonomous vehicles), from the risk of operating in unknown or perilous environments (cf. rescue scenarios), or to support timely decision-making in complex settings (cf. data-centre operations). Beyond the results that individual autonomous agents can carry out, a further opportunity lies in the collaboration of multiple agents or robots. Emerging macro-paradigms provide an approach to programming whole collectives towards global goals. Aggregate computing is one such paradigm, formally grounded in a calculus of computational fields enabling functional composition of collective behaviours that could be proved, under certain technical conditions, to be self-stabilising. In this work, we address the concept of collective autonomy, i.e., the form of autonomy that applies at the level of a group of individuals. As a contribution, we define an agent control architecture for aggregate multi-agent systems, discuss how the aggregate computing framework relates to both individual and collective autonomy, and show how it can be used to program collective autonomous behaviour. We exemplify the concepts through a simulated case study, and outline a research roadmap towards reliable aggregate autonomy.

scholarly journals Web platform using digital image processing and geographic information system tools: a Brazilian case study on dengue

2015 ◽  
Vol 14 (1) ◽  
Author(s):  
Lourdes M Brasil ◽  
Marília M F Gomes ◽  
Cristiano J Miosso ◽  
Marlete M da Silva ◽  
Georges D Amvame-Nze
Keyword(s):  
Image Processing ◽  
Information System ◽  
Geographic Information System ◽  
Digital Image Processing ◽  
Digital Image ◽  
Geographic Information ◽  
Web Platform ◽  
Brazilian Case

Exploring management strategies for community-based forests using multi-agent systems: A case study in Palawan, Philippines

2009 ◽  
Vol 90 (11) ◽  
pp. 3607-3615 ◽  
Author(s):  
Paolo C. Campo ◽  
Guillermo A. Mendoza ◽  
Philippe Guizol ◽  
Teodoro R. Villanueva ◽  
François Bousquet
Keyword(s):  
Management Strategies ◽  
Multi Agent Systems ◽  
Community Based ◽  
Agent Systems ◽  
Multi Agent

AN AGENT-ORIENTED APPROACH FOR IMAGE CLASSIFICATION WITH ICA-COLOR SIFT

2012 ◽  
Vol 21 (02) ◽  
pp. 1240003
Author(s):  
MOHAMMAD KHAZAB ◽  
DAN-NI AI ◽  
JEFFREY TWEEDALE ◽  
YEN-WEI CHEN ◽  
LAKHMI JAIN
Keyword(s):  
Image Processing ◽  
Image Classification ◽  
Classification Task ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent ◽  
Flexible Framework ◽  
Event Based ◽  
Oriented Approach

This paper discusses the research conducted on developing a Multi-Agent System (MAS) for solving an image classification task. The aim of this research is to equip agents in MAS with reusable autonomous capabilities. The system provides a flexible framework for developing the communication aspects within an agent-oriented architecture to program agents that dynamically acquire functionality at runtime using event based messaging. In this research agents are equipped with unique image processing capabilities and required to interact and cooperate to achieve the goal. Complementary research on a variety of agent tools (specifically JACK, JADE and CIAgent) and communication languages (ACL, KQML, FIPA and SOAP) has been reviewed to glean knowledge that enables these agents to adapt those capabilities. The system has generated encouraging results.

Multi-agent scavenging patterns in Hawai‘i: A forensic archaeological and skeletal case study

2021 ◽  
Vol 61 (6) ◽  
pp. 723-734
Author(s):  
Jennifer F. Byrnes ◽  
William R. Belcher
Keyword(s):  
Multi Agent
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