Biomedical Image Processing: Techniques, Applications and Recent Research Trends – A Review
Abstract
Biomedical image processing is an necessary component of modern healthcare systems. Images of medical acquireed from various imaging modalities provide important diagnostic information, but these images often face issues from noise, artifacts, and low contrast. Image processing techniques help improve image quality and enable automated disease detection and clinical analysis. This review paper outlines the fundamental stages in biomedical image processing such as feature extraction, segmentation, preprocessing feature classification and image acquisation. It looks at both modern deep learning methods and conventional processing of images. A comparative discussion of different segmentation approaches and commonly used evaluation metrics is also presented. The paper further highlights current challenges and emerging research directions in biomedical imaging systems.
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