mlsanityData to 14 Oct 2026

Recent Advancements in Microscopy Image Enhancement using Deep Learning: A Survey

arXiv 2509.15363 ↗First posted 18 Sep 2025eess.IV cs.AI cs.CVcited by 1

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Abstract (arXiv)

Microscopy image enhancement plays a pivotal role in understanding the details of biological cells and materials at microscopic scales. In recent years, there has been a significant rise in the advancement of microscopy image enhancement, specifically with the help of deep learning methods. This survey paper aims to provide a snapshot of this rapidly growing state-of-the-art method, focusing on its evolution, applications, challenges, and future directions. The core discussions take place around the key domains of microscopy image enhancement of super-resolution, reconstruction, and denoising, with each domain explored in terms of its current trends and their practical utility of deep learning.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 22 of its 50 references that are in the map. First posted on arXiv 18 Sep 2025.

Builds on

22 of 50 references.

References · 22

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10 more
  1. 2020Medical image reconstruction with image-adaptive priors learned by use of generative adversarial networkscited by 11
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Citing papers per year: 2026: 1.

1 paper.

  1. 2026A Scale-adaptive Vision Model Links C. elegans Neuronal Morphology to Behavior for Neurotoxicity Assessmentcited by 0