Texture Analysis Application in Medicine
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Biomedical Engineering".
Deadline for manuscript submissions: closed (15 March 2024) | Viewed by 172
Special Issue Editor
Interests: machine learning; deep neural network architectures; medical image analysis; emotional state analysis;
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Disease determination and treatment suggestions are based on uni- or multimodal medical image analysis, such as computed tomography, magnetic resonance imaging and many others. Nowadays, visual inspection of these data makes the diagnosis dependent on the physicist's experience and training. Yet, computer-aided medicine endeavours to establish comparable solutions between medical centres, assuring high standards. Therefore, the progress and automatization of medical image understanding are necessary to support technological development in this domain.
Several medical data analysis methods based on texture analysis have been developed in recent years, leading to significant advances in the field. The automatic analysis of medical data is one of the most active areas in computer vision research. However, deep learning technologies try to limit the influence of traditional machine learning approaches where the features must be determined beforehand, but there is still a need for such solutions. This Special Issue seeks original technical and review papers on the latest applications of texture analysis in medicine. Topics of interest include, but not limited to, the following:
- Medical image processing and understanding
- Computed tomography
- Micro-computed tomography
- Cone beam computed tomography
- Optical coherence tomography
- Magnetic resonance
- Ultrasonography
- Whole-slide imaging
- Computer-aided diagnosis
Dr. Karolina Nurzynska
Guest Editor
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Keywords
- texture analysis
- medical image understanding
- computer-aided diagnosis
- imaging
- computer vision
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