Computational and Mathematical Methods in Medicine

Machine Learning and Artificial Intelligence Methods in Computer Vision and Visualization for Healthcare


Publishing date
01 Apr 2022
Status
Closed
Submission deadline
19 Nov 2021

Lead Editor
Guest Editors

1University of Canterbury, Christchurch, New Zealand

2China University of Petroleum, Qingdao, China

3University of Nottingham, Malaysia Campus, Semenyih, Malaysia

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

Machine Learning and Artificial Intelligence Methods in Computer Vision and Visualization for Healthcare

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

Description

Visualization, particularly scientific visualization, provides unbeatable mechanisms to communicate different aspects of data. It broadly includes several important computer science research fields, including computer graphics, computer vision, and visual computing. With the growing advances in artificial intelligence (AI), machine learning algorithms are increasingly being integrated with visualization and computer vision methods. Owing to the fact that new technologies enable many non-intrusive, wearable, multi-modal, and sensor-based devices to be used in healthcare-related data collection, the data obtained from these processes provides a promising opportunity for many visualization and computer vision methods to be put in place. Those data often have some unique characteristics, including sensitivity, high practical value, complexity, large size, and multi-dimensionality, which makes the research exploration even more intriguing. The combination of visualization, computer vision, and machine learning facilitates the creation of efficient approaches, applications, and even systems in healthcare.

Machine learning/AI-based computer vision methods have been developed for the diagnosis of tumors and nodules appearing in different human organs using image data obtained using different scan modalities, such as CT and MRI. Some of the results are promising, yet there is still room for improvement. Machine learning/AI techniques can be used for feature extraction and classification of non-image healthcare data, which is often neglected. The non-image data can include text-based patient records, doctors' prescriptions, medicine descriptions, and diagnosis results. This can be an important exploration of the capability of ML/AI, as visualization created for non-image healthcare data increases the practical value of the data.

This Special Issue aims to cover recent advancements in visualization and computer vision using machine learning and AI with a particular interest in healthcare data and its open problems. The objective is to provide a comprehensive and up-to-date collection of research and experimental works in the field. We welcome both original research and review articles.

Potential topics include but are not limited to the following:

  • Visualization-based predictive analytics and therapy
  • Medical image processing and computer vision
  • Novel visualization algorithms using healthcare data
  • Machine learning-enriched visualization methods
  • Single and multi-dimensional medical image analysis
  • Visualization of e-health data
  • Cloud and big data visualization for healthcare
  • Clinical/patient record visualization
  • Patient behavior data visualization and analysis
  • Visualization and machine learning in assistive technology
  • Visualization-aided diagnosis and prediction
  • Symptom-related pattern detection and recognition
  • Visualization-guided medical procedures
  • Medical data (image and non-image) feature extraction

Articles

  • Special Issue
  • - Volume 2022
  • - Article ID 3812509
  • - Research Article

Accurate 3D Reconstruction of White Matter Hyperintensities Based on Attention-Unet

Xun Wang | Lisheng Wang | ... | Xiaoya Feng
  • Special Issue
  • - Volume 2022
  • - Article ID 8501828
  • - Research Article

Compound W-Net with Fully Accumulative Residual Connections for Liver Segmentation Using CT Images

Mahmoud Abdelazim Khattab | Iman Yi Liao | ... | Siang Yew Chong
  • Special Issue
  • - Volume 2022
  • - Article ID 7137524
  • - Research Article

Investigating the Role of Image Fusion in Brain Tumor Classification Models Based on Machine Learning Algorithm for Personalized Medicine

R. Nanmaran | S. Srimathi | ... | M. Muhibbullah
  • Special Issue
  • - Volume 2022
  • - Article ID 4295985
  • - Research Article

Functional Magnetic Resonance Imaging Study of Electroacupuncture Stimulating Uterine Acupoints

ChengChao Xu | XiaoHua Yu | ... | TianYu Bai
  • Special Issue
  • - Volume 2021
  • - Article ID 9773917
  • - Research Article

RDFNet: A Fast Caries Detection Method Incorporating Transformer Mechanism

Hao Jiang | Peiliang Zhang | ... | Bo Jin
  • Special Issue
  • - Volume 2021
  • - Article ID 9025470
  • - Review Article

Deep Learning in Cancer Diagnosis and Prognosis Prediction: A Minireview on Challenges, Recent Trends, and Future Directions

Ahsan Bin Tufail | Yong-Kui Ma | ... | Rahim Khan
  • Special Issue
  • - Volume 2021
  • - Article ID 3440778
  • - Research Article

Sentiment Analysis Based on the Nursing Notes on In-Hospital 28-Day Mortality of Sepsis Patients Utilizing the MIMIC-III Database

Qiaoyan Gao | Dandan Wang | ... | Wenfeng Wang
  • Special Issue
  • - Volume 2021
  • - Article ID 2747274
  • - Research Article

Segmentation and Automatic Identification of Vasculature in Coronary Angiograms

Yaofang Liu | Wenlong Wan | ... | Qing Zhang
  • Special Issue
  • - Volume 2021
  • - Article ID 2602688
  • - Research Article

Automatic Assessment of Mitral Regurgitation Severity Using the Mask R-CNN Algorithm with Color Doppler Echocardiography Images

Qinglu Zhang | Yuanqin Liu | ... | Xiangming Zhu
  • Special Issue
  • - Volume 2021
  • - Article ID 1562502
  • - Research Article

Clinical Significance of Hyperdense Lesions on Non-enhanced Brain CT Obtained Immediately after Arterial Revascularization in Acute Ischemic Stroke Patients

Changbin Wang | Zudong Yin | ... | Xiumin Zhao
Computational and Mathematical Methods in Medicine
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Article of the Year Award: Outstanding research contributions of 2021, as selected by our Chief Editors. Read the winning articles.