Guided sparse decomposition with anisotropic fusion for medical image enhancement.

ABSTRACT:

Background

Medical imaging plays a crucial role in modern healthcare by providing essential insights for accurate diagnosis and effective treatment planning across a variety of diseases. However, enhancing these images while preserving critical structural details presents significant challenges, as existing techniques often compromise vital information during the enhancement process. This study aimed to develop an efficient and artifact-free image enhancement method to improve both tonal clarity and detail preservation in medical images, thereby enhancing their diagnostic utility.

Methods

We proposed a novel method, named guided sparse decomposition with anisotropic fusion (GSDAF), which improves upon the traditional guided image filter (GIF) by introducing a weighted sparse

SUBMITTER: Bian W 

PROVIDER: S-EPMC12514588 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature