INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY

Scope & Guideline

Exploring the Frontiers of Imaging Science

Introduction

Delve into the academic richness of INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY with our guidelines, detailing its aims and scope. Our resource identifies emerging and trending topics paving the way for new academic progress. We also provide insights into declining or waning topics, helping you stay informed about changing research landscapes. Evaluate highly cited topics and recent publications within these guidelines to align your work with influential scholarly trends.
LanguageEnglish
ISSN0899-9457
PublisherWILEY
Support Open AccessNo
CountryUnited States
TypeJournal
Convergefrom 1989 to 1992, from 1994 to 2000, from 2002 to 2024
AbbreviationINT J IMAG SYST TECH / Int. J. Imaging Syst. Technol.
Frequency6 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address111 RIVER ST, HOBOKEN 07030-5774, NJ

Aims and Scopes

The INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY focuses on the convergence of advanced imaging technologies and innovative computational techniques to enhance medical diagnostics and treatment outcomes. Its core research areas encompass various imaging modalities, machine learning applications, and the integration of computational methods for medical image analysis.
  1. Medical Imaging Techniques:
    The journal emphasizes the development and application of diverse medical imaging modalities, including MRI, CT, ultrasound, and PET, to improve diagnostic accuracy and treatment planning.
  2. Deep Learning and AI Applications:
    A substantial focus is placed on the use of deep learning and artificial intelligence to automate and enhance image analysis, classification, and segmentation tasks in various medical contexts.
  3. Multimodal Imaging and Fusion:
    The journal explores the integration of multiple imaging modalities to provide comprehensive diagnostic information, enhancing the understanding of complex medical conditions.
  4. Image Processing and Enhancement Techniques:
    Research on innovative algorithms and techniques for image processing, enhancement, and segmentation is a key area, aiming to improve the quality and interpretability of medical images.
  5. Clinical Applications and Outcomes:
    The journal also emphasizes studies that bridge the gap between imaging technology and clinical practice, showcasing how advancements in imaging systems can lead to better patient outcomes.
The journal has identified several emerging themes and trends that highlight the evolving landscape of medical imaging and technology. These trends indicate a shift towards more integrated, intelligent, and patient-centered imaging solutions.
  1. Federated Learning and Privacy-Preserving Techniques:
    With the increasing emphasis on patient data privacy, there is a growing trend in research focusing on federated learning models that allow collaborative learning without sharing sensitive data.
  2. Explainable AI in Medical Imaging:
    There is an emerging focus on explainable AI techniques that enhance the interpretability of deep learning models, ensuring that clinicians can understand and trust AI-driven diagnostic recommendations.
  3. Integration of Augmented and Virtual Reality:
    Research exploring the applications of augmented reality (AR) and virtual reality (VR) in medical imaging and training is gaining traction, offering innovative ways to visualize and interact with complex data.
  4. Telemedicine and Remote Diagnostics:
    The rise of telemedicine has led to an increase in studies focusing on remote diagnostic capabilities, utilizing imaging technologies to facilitate off-site consultations and patient monitoring.
  5. Real-Time Imaging and Analysis:
    There is a trend towards developing real-time imaging systems capable of immediate analysis, which is particularly relevant in surgical and emergency settings where timely decision-making is crucial.

Declining or Waning

While the journal continues to thrive in many areas, certain themes have shown a decline in prominence over recent years. These waning scopes reflect shifts in research focus and technological advancements.
  1. Traditional Image Analysis Techniques:
    There is a noticeable decrease in publications focused on conventional image analysis methods, as researchers increasingly shift towards machine learning and AI-driven approaches.
  2. Basic Imaging Hardware Innovations:
    Research centered on fundamental hardware innovations for imaging systems has diminished, as the field increasingly prioritizes software advancements and algorithmic improvements.
  3. Manual and Semi-Automated Techniques:
    The reliance on manual and semi-automated techniques for image analysis has waned, giving way to fully automated systems powered by AI and deep learning, reflecting a broader trend towards automation in medical imaging.

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