BioMed Research International

Artificial Intelligence for Medical Image Analysis


Publishing date
01 Jul 2021
Status
Closed
Submission deadline
12 Mar 2021

Lead Editor

1Northwestern Polytechnical University, Xi'an, China

2The Commonwealth Scientific and Industrial Research Organisation, Sydney, Australia

3University of Tokyo, Tokyo, Japan

4University of Leicester, Leicester, UK

This issue is now closed for submissions.
More articles will be published in the near future.

Artificial Intelligence for Medical Image Analysis

This issue is now closed for submissions.
More articles will be published in the near future.

Description

Artificial intelligence (AI) and its applications are among the most investigated research areas. Over recent years, we have witnessed AI revolutionising all kinds of medical imaging, including X-ray, ultrasound, computerised tomography (CT), MRI, fMRI, positron emission tomography (PET), and single photon emission computed tomography (SPECT). Numerous AI-based tools have been developed to automate medical image analysis and improve automated image interpretation.

Modern medical imaging provides an increasing number of features derived from different types of analysis, including artificial intelligence. These features are most often used for a variety of analyses, including deep learning, fuzzy sets, rough sets, uncertain analysis, multi-objective optimisation, swarm intelligence optimisation, and machine learning. The results of these analyses can be used as a reference for the evaluation of patients by medical teams. A further challenge of AI-driven solutions is the development of tools for personalised disease assessment through AI models by taking advantage of their ability to learn patterns and relationships in medical images, utilising massive volumes of medical images.

This Special Issue aims to promote the latest cutting-edge AI-driven research in medical image processing and analysis, with the aforementioned approaches in mind. Of particular interest are submissions regarding novel algorithms, architectures, techniques, and applications of AI for medical image analysis. However, contributions concerning other aspects of medical image processing (including, but not limited to, image quality improvement, image reconstruction, image restoration, image registration, image segmentation, and image feature extraction, to tackle the variations in image spatial-temporal resolution, as well as the diversity of biophysical-biochemical mechanisms) are also welcomed. We invite investigators to contribute original research articles as well as review articles that will address the challenges facing artificial intelligence approaches in medical image analysis.

Potential topics include but are not limited to the following:

  • Deep learning models for medical image reconstruction, restoration, registration, segmentation, classification, visualisation, and prediction
  • Fuzzy sets (fuzzy relations) in medical image analysis
  • Rough sets in medical image analysis
  • Uncertain analysis in medical image analysis
  • Multi-objective optimisation in medical image analysis
  • Swarm intelligence optimisation in medical image analysis
  • Machine learning-based integrated concepts and solutions in medical image analysis
  • Data security and user privacy solutions for medical image analysis

Articles

  • Special Issue
  • - Volume 2021
  • - Article ID 5566885
  • - Research Article

Assessment of MRI-Based Radiomics in Preoperative T Staging of Rectal Cancer: Comparison between Minimum and Maximum Delineation Methods

Haidi Lu | Yuan Yuan | ... | Jianping Lu
  • Special Issue
  • - Volume 2021
  • - Article ID 6671417
  • - Review Article

A State-of-the-Art Review for Gastric Histopathology Image Analysis Approaches and Future Development

Shiliang Ai | Chen Li | ... | Hong Li
  • Special Issue
  • - Volume 2021
  • - Article ID 5561125
  • - Research Article

Multichannel Retinal Blood Vessel Segmentation Based on the Combination of Matched Filter and U-Net Network

Yuliang Ma | Zhenbin Zhu | ... | Wanzeng Kong
  • Special Issue
  • - Volume 2021
  • - Article ID 5584004
  • - Research Article

Diagnosis of Cervical Cancer based on Ensemble Deep Learning Network using Colposcopy Images

Venkatesan Chandran | M. G. Sumithra | ... | S. Manoharan
  • Special Issue
  • - Volume 2021
  • - Article ID 6681092
  • - Research Article

Hepatic Alveolar Echinococcosis: Predictive Biological Activity Based on Radiomics of MRI

Bo Ren | Jian Wang | ... | Aierken Aikebaier
  • Special Issue
  • - Volume 2021
  • - Article ID 5548517
  • - Research Article

Coronary Vessel Segmentation by Coarse-to-Fine Strategy Using U-nets

Le Nhi Lam Thuy | Tan Dat Trinh | ... | Pham The Bao
  • Special Issue
  • - Volume 2021
  • - Article ID 5562801
  • - Research Article

A Segmentation of Melanocytic Skin Lesions in Dermoscopic and Standard Images Using a Hybrid Two-Stage Approach

Yoo Na Hwang | Min Ji Seo | Sung Min Kim
  • Special Issue
  • - Volume 2021
  • - Article ID 5519144
  • - Research Article

CT Texture Analysis for Preoperative Identification of Lymphoma from Other Types of Primary Small Bowel Malignancies

Shunli Liu | Chuanyu Zhang | ... | Zaixian Zhang
  • Special Issue
  • - Volume 2021
  • - Article ID 8865237
  • - Research Article

18F-FDG-PET/CT Whole-Body Imaging Lung Tumor Diagnostic Model: An Ensemble E-ResNet-NRC with Divided Sample Space

Zhou Tao | Huo Bing-qiang | ... | Ding Hongsheng
  • Special Issue
  • - Volume 2021
  • - Article ID 6657566
  • - Research Article

Association between CT-Quantified Body Composition and Recurrence, Survival in Nonmetastasis Colorectal Cancer Patients Underwent Regular Chemotherapy after Surgery

Piaopaio Ying | Wenyi Jin | ... | Weiyang Cai
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