AIMIA2020: Applied Intelligence for Medical Image Analysis

Applied Intelligence for Medical Image Analysis

Over the last decades, there has been a revolution in the analysis of medical images with uprising technological advancement. Vivid intelligent technologies have been developed to analyze and interpret medical images automatically. To exemplify, the performance illustrated by the deep learning methods in the disease diagnosis is remarkable. Moreover, the availability of a massive number of medical images and other forms of medical data have advantages in applying intelligence to develop personalized tools for disease assessment and combat new diseases.

With the above mentioned in mind, this book aims at the latest cutting-edge research in medical image analysis. Particularly, submissions will be regarding the computer-aided diagnosis and improvement in image analysis and interpretation. However, other aspects of medical image analysis including, but not limited to, image quality improvement, image restoration, image segmentation, image registration, radiomics analysis are also welcomed.

List of Topics

1. A survey on intelligent tools and techniques used for various medical imaging applications 

2. Automated image analysis of Covid 19 prediction and drug development by medical images like x-ray, CT scan, Ultrasound, and others.

3. New histopathological image analysis methods for cell segmentation and quantification

   1. Deep learning-based cell segmentation methods 

   2. Traditional cell segmentation methods

4. Novel disease identification/classification methods using various types of medical images like histopathological  images, radiological images, and others 

   1. Classical/Deep learning-based classification methods 

   2. Identification/detection of inflamed tissue images

5. Use of Bio-inspired Algorithms in the field of medical imaging

   1. Development of new bio-inspired algorithms based feature selection methods for efficient analysis of medical images

   2. Development of new bio-inspired algorithms based  clustering methods for medical image analysis 

   3. Other techniques based on Bio-inspired algorithms for medical image analysis

6. Cloud Computing approaches for medical image analysis

   1. Medical image data handling using cloud computing

   2. New parallel methods for handling big data of medical images

Note: Any other topic related to intelligent methods for medical image analysis which are not mentioned above will be considered for the proposed book.

Publication

AIMIA2020 proceedings will be published in Apple press (AAP)

All AAP books are sent to Scopus/ISI, Google Books, Google Scholar, etc.

Indexing & Abstracting Info from Taylor & Francis:

AAP is in the process of rolling out chapter level DOIs to all our publications, and we will shortly be able to enrich our metadata feed to Crossref to include references at the book level (chapter level will take longer – there are rather a lot!). This means it will be easier for WoS (Web of Science), etc to pick up citations to our books.

WoS and Scopus both index at the chapter level already (they deconstruct our pdfs at present. We’re hoping they will start accepting an XML digital feed in the next year as that will reduce errors and make everything run more smoothly).

Submission Guidelines

The chapter must be original and not simultaneously submitted to another journal or conference. Kindly adhere to the following guidelines:

• Generally, manuscripts should be either 15-20 pages for a single column or 10-15 pages for double columns, 1.5 line spaced, using 11 point font in Times New Roman.
• Microsoft Word is preferred. You may use MathType for equations. Please request prior approval for manuscripts in any other format.
• You can download the following template for chapter preparation:
  • Microsoft Word Template
• All chapter must be submitted through easychair on the following link:
  • Submit Chapter 

Editors

1. Dr. Aarti, Lovely Professional University, Jalandhar, Punjab, India
2. Dr. Raju Pal, Jaypee Insitute of Information Technology, Noida, U.P., India
3. Dr. Mukesh Saraswat, Jaypee Insitute of Information Technology, Noida, U.P., India
4. Dr. Himanshu Mittal, Jaypee Insitute of Information Technology, Noida, U.P., India

Contact

All questions about submissions should be emailed to: aimia.easychair@gmail.com