AI for Visual Perception and Artificial Consciousness

A special issue of Journal of Imaging (ISSN 2313-433X). This special issue belongs to the section "AI in Imaging".

Deadline for manuscript submissions: closed (31 May 2024) | Viewed by 1571

Special Issue Editors


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Guest Editor
Department of Business, Law, Economics and Consumption, Faculty of Communication, IULM University, 20143 Milan, Italy
Interests: computer vision; artificial intelligence; deep learning; image analysis and processing; visual saliency; biomedical image analysis; large language models
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Guest Editor
Dipartimento di Scienze Umanistiche, Universitá degli Studi di Palermo, 90133 Palermo, Italy
Interests: computational linguistics; NLP; cognitive robotics; artificial consciousness

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Guest Editor
Department of Business, Law, Economics and Consumer Behaviour 'Carlo A. Ricciardi', Faculty of Communication, IULM University, 20143 Milan, Italy
Interests: philosophy of mind; consciousness; machine consciousness; psychology of perception; psychology of art; media; philosophy of communication
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Guest Editor
National Reseach Council of Italy (CNR), ISASI Institute of Applied Sciences & Intelligent Systems, 80078 Pozzuoli, Italy
Interests: multimedia signal processing; image processing and understanding; image feature extraction and selection; neural network classifiers; object classification and tracking
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Guest Editor
Institute for High Performance Computing and Networking (ICAR), National Research Council (CNR), 90146 Palermo, Italy
Interests: cognitive architectures; augmented human–computer interaction; social robotics

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Guest Editor
Institute for High Performance Computing and Networking (ICAR), National Research Council (CNR), 90146 Palermo, Italy
Interests: robotics; computer vision; computational creativity
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Despite recent progress, AI still faces fundamental problems at the intersection of technology and perception. AI can help us gain deeper insights into visual perception and consciousness.

Visual perception refers to how living beings, including humans, interpret and make sense of visual stimuli from the surrounding environment. It spans the reception of visual information through the eyes, the processing of this information by the brain, and the subsequent construction of a meaningful perceptual experience.

On the other hand, artificial consciousness considers the possibility of designing machines or artificial systems associated with forms of consciousness or subjective experience. Today, AI can reliably recognise a face, but can it see it? Is AI able to identify itself by visually self-perceiving itself? Does conscious awareness compare favourably to what today's AI can do? Are we missing a key component?

The Special Issue aims to gather contributions in the form of research and review articles encompassing the multidisciplinary topics involved in artificial intelligence for perception and artificial consciousness.

A non-exhaustive list of topics of interest is given below:

  • AI models for perception
  • AI models for visual attention
  • Attention and self-attention-based applications
  • Computational approaches for visual saliency
  • Consciousness and artificial consciousness ontology
  • Computational models of consciousness
  • Cognitive architectures for artificial consciousness
  • Biologically inspired AI solutions
  • Saliency from images and videos

Dr. Alessandro Bruno
Dr. Arianna Pipitone
Prof. Dr. Riccardo Manzotti
Dr. Pier Luigi Mazzeo
Dr. Agnese Augello
Dr. Filippo Vella
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Imaging is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • visual perception
  • artificial consciousness
  • visual attention
  • artificial intelligence
  • saliency models

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Published Papers (1 paper)

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Research

13 pages, 4234 KiB  
Article
AI Use in Mammography for Diagnosing Metachronous Contralateral Breast Cancer
by Mio Adachi, Tomoyuki Fujioka, Toshiyuki Ishiba, Miyako Nara, Sakiko Maruya, Kumiko Hayashi, Yuichi Kumaki, Emi Yamaga, Leona Katsuta, Du Hao, Mikael Hartman, Feng Mengling, Goshi Oda, Kazunori Kubota and Ukihide Tateishi
J. Imaging 2024, 10(9), 211; https://doi.org/10.3390/jimaging10090211 - 28 Aug 2024
Viewed by 856
Abstract
Although several studies have been conducted on artificial intelligence (AI) use in mammography (MG), there is still a paucity of research on the diagnosis of metachronous bilateral breast cancer (BC), which is typically more challenging to diagnose. This study aimed to determine whether [...] Read more.
Although several studies have been conducted on artificial intelligence (AI) use in mammography (MG), there is still a paucity of research on the diagnosis of metachronous bilateral breast cancer (BC), which is typically more challenging to diagnose. This study aimed to determine whether AI could enhance BC detection, achieving earlier or more accurate diagnoses than radiologists in cases of metachronous contralateral BC. We included patients who underwent unilateral BC surgery and subsequently developed contralateral BC. This retrospective study evaluated the AI-supported MG diagnostic system called FxMammo™. We evaluated the capability of FxMammo™ (FathomX Pte Ltd., Singapore) to diagnose BC more accurately or earlier than radiologists’ assessments. This evaluation was supplemented by reviewing MG readings made by radiologists. Out of 1101 patients who underwent surgery, 10 who had initially undergone a partial mastectomy and later developed contralateral BC were analyzed. The AI system identified malignancies in six cases (60%), while radiologists identified five cases (50%). Notably, two cases (20%) were diagnosed solely by the AI system. Additionally, for these cases, the AI system had identified malignancies a year before the conventional diagnosis. This study highlights the AI system’s effectiveness in diagnosing metachronous contralateral BC via MG. In some cases, the AI system consistently diagnosed cancer earlier than radiological assessments. Full article
(This article belongs to the Special Issue AI for Visual Perception and Artificial Consciousness)
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