Biomedical imaging is an active area of research involving different techniques for acquiring, analyzing, and interpreting images that capture various biomedical aspects of living beings. With recent advances in sensor technology and artificial intelligence (AI), research in this field has garnered global attention and is rapidly gaining momentum.

The commonly used biomedical image modalities include computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), X-ray, and ultrasound imaging. Automated systems for image analysis, interpretation, and classification can assist physicians in swiftly arriving at an accurate diagnosis by capturing relevant information from biomedical images.

This Methods Collection aims to provide an interdisciplinary, international forum for publishing papers in all areas of biomedical imaging, emphasizing popular existing techniques and promising upcoming trends. Authors are welcome to submit their scientific contributions and experimental research in developing next-generation biomedical imaging systems.

Topics of interest include, but are not limited to, the following:

1. Interpretation and analysis of biomedical images using deep learning techniques
2. AI in automated disease detection using biomedical images
3. Content-based image retrieval for biomedical images
4. Next-generation imaging techniques for biomedical applications
5. Novel feature extraction frameworks for biomedical images
6. Imaging-based continuous patient health monitoring systems
7. Image analysis and emerging applications in biomedical engineering