Computational and Mathematical Methods in Medicine

Artificial Intelligence and Cognitive Computing in Medical Image Processing


Publishing date
01 Jan 2022
Status
Closed
Submission deadline
20 Aug 2021

Lead Editor

1Universiti Putra Malaysia, Serdang, Malaysia

2University of Malaya , Kuala Lumpur, Malaysia

3Shahid Beheshti University, Tehran, Iran

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

Artificial Intelligence and Cognitive Computing in Medical Image Processing

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

Description

Medical imaging has been positively affected by key developments in artificial intelligence (AI) and cognitive computing in recent years. In particular, advanced AI algorithms, such as deep learning, have found numerous applications in the field of medical image processing and analysis, ranging from image reconstruction, tumor detection, feature extraction, segmentation, and classification, to wound healing assessment and revealing cardiovascular abnormalities. Other applications include the diagnosis of neurological conditions, flagging thoracic complications and conditions, physical simulation, breast imaging, and the computation of diabetic retinopathy severity. These applications have all been significantly advanced due to the substantial strides in perception made by AI. The latest developments in deep learning have shown that those tasks distinctly linked to perception, including segmentation, detection, and recognition, are well handled by the employment of state-of-the-art architectures such as computer vision, even in the absence of prior knowledge. In addition, the inherent compatibility of deep learning methods to various classical approaches and to each other makes the end-to-end training of algorithms possible by using fusion on a network level. Specifically, the convolutional neural network (CNN) architectures that have emerged from deep learning have demonstrated high-computational efficiency and enable multi-task learning by integrating with classical algorithms. Similarly, cognitive computing/intelligence, comprising of self-learning and reasoning techniques that enable computers to mimic human intelligence, has demonstrated remarkable progress in the field of clinical image analysis. They can support and augment human decision making in cases of complexity, uncertainty, and high information volume.

However, there are key barriers limiting the practical applications of AI and cognitive computing in the field of medical imaging. The regulatory process remains challenging, particularly for machine learning-based products, there is a need for large-scale validation studies to be conducted to show the performance of AI algorithms and for the underlying computing technology to be tested in clinical environments, and there is a lack of integration of the results of AI-based analysis tools into clinical workflows.

Therefore, this Special Issue aims to focus primarily on novel AI and cognitive computing algorithms and methods proposed for medical image analysis, to highlight the current challenges for practical applications of AI and cognitive computing in clinical environments, and to propose possible solutions for overcoming the barriers stopping AI becoming the mainstream in medical imaging.

Potential topics include but are not limited to the following:

  • Integration of cognitive computing and AI in medical image processing
  • Challenges of adopting AI-based medical image analysis
  • Artificial intelligence in medical image analysis (feature extraction, segmentation, classification, and reliable measurements)
  • Medical image analysis of the breast, retina, lungs, heart, nerves, musculoskeletal system, and abdomen using AI
  • Feature extraction in medical imaging using machine learning/ deep learning/ convolutional neural networks
  • Machine learning/deep learning/convolutional neural networks in lesion, organ, and substructure segmentation
  • Machine learning-based lesion segmentation methods from MRI/CT/ultrasound images
  • Object/lesion detection and classification using machine learning /deep learning/ neural networks/ evolutionary computation
  • Medical image registration using artificial intelligence techniques
  • Artificial intelligence in medical image reconstruction
  • Cognitive computing applications in medical image processing and analysis (feature extraction, segmentation, classification, and reliable measurements)
  • Artificial intelligence/cognitive science in automatic diagnostic systems
  • Artificial intelligence/cognitive science in revealing cardiovascular abnormalities and diagnosis of neurological conditions

Articles

  • Special Issue
  • - Volume 2022
  • - Article ID 7746991
  • - Research Article

MR Image Classification for Brain Tumor Texture Based on Pseudo-Label Learning and Optimized Feature Extraction

Qianqian Xu | Huachang Xu | ... | Hong Zhu
  • Special Issue
  • - Volume 2022
  • - Article ID 7003272
  • - Research Article

A Broad Learning System to Predict the 28-Day Mortality of Patients Hospitalized with Community-Acquired Pneumonia: A Case-Control Study

Jing Yuan | Xin Liu | ... | Jing-Jing Zhang
  • Special Issue
  • - Volume 2022
  • - Article ID 1558607
  • - Research Article

A Hemolysis Image Detection Method Based on GAN-CNN-ELM

Xiaonan Shi | Yong Deng | ... | Limei Fu
  • Special Issue
  • - Volume 2021
  • - Article ID 7822119
  • - Research Article

Development and Validation of Prediction Model for High Ovarian Response in In Vitro Fertilization-Embryo Transfer: A Longitudinal Study

Xinsha Tan | Honglin Xi | ... | Wenfeng Wang
  • Special Issue
  • - Volume 2021
  • - Article ID 3900254
  • - Research Article

An Approach for Thoracic Syndrome Classification with Convolutional Neural Networks

Sapna Juneja | Abhinav Juneja | ... | Sandeep Kautish
  • Special Issue
  • - Volume 2021
  • - Article ID 6953593
  • - Research Article

Multistage Optimization Using a Modified Gaussian Mixture Model in Sperm Motility Tracking

Mohammed Alameri | Khairunnisa Hasikin | ... | Muhammad Mokhzaini Azizan
  • Special Issue
  • - Volume 2021
  • - Article ID 2973108
  • - Research Article

Low-Dose CT Image Denoising with Improving WGAN and Hybrid Loss Function

Zhihua Li | Weili Shi | ... | Zhengang Jiang
  • Special Issue
  • - Volume 2021
  • - Article ID 3859386
  • - Research Article

Algorithm of Pulmonary Vascular Segment and Centerline Extraction

Shi Qiu | Jie Lian | ... | Ting Liang
  • Special Issue
  • - Volume 2021
  • - Article ID 5095940
  • - Research Article

Comparison of Diagnostic Performance between Perfusion-Related Intravoxel Incoherent Motion DWI and Dynamic Contrast-Enhanced MRI in Rectal Cancer

Ming Li | Xiaodan Xu | ... | Zhihua Lu
  • Special Issue
  • - Volume 2021
  • - Article ID 7259414
  • - Research Article

CT Image Analysis and Clinical Diagnosis of New Coronary Pneumonia Based on Improved Convolutional Neural Network

Wu Deng | Bo Yang | ... | Jia Xu
Computational and Mathematical Methods in Medicine
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