AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
The experimental results demonstrate that the proposed sequential framework provides superior contrast enhancement, noise suppression, structural preservation, and perceptual quality while maintaining diagnostically relevant anatomical information.
An image-processing-based technique for identifying and segmenting lesion regions in dental X-ray images is described in this research. The low contrast of these images and the similarity in intensity between lesion sites and surrounding tissues continue to make accurate detection difficult. Image enhancement approache...
An adaptive cluster-wise progressive denoising algorithm for maintaining detail in medical images that outperforms existing denoising methods in terms of noise suppression while conserving critical anatomical characteristics.
The improvement techniques for X-ray images based on the spatial domain include gamma modification, balance enhancement of contrast, image invert/compliment, super-resolution, contrasting-limited adaptive histogram equalization, and improvement with spatial filtering.
Panoramic dental X-rays are the most common imaging source for oral conditions; however, their reading is often delayed by artefacts, and poor contrast. A precise segmentation of dental structures represents the core for clinical diagnosis and treatment planning; yet, current solutions frequently fail to generalize and...
The Gaussian filter successfully lowers noise and greatly improves image contrast, making these techniques useful for the precise and early identification of breast cancer in mammograms.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.