Microscopic image enhancement for accurate sickle cell disease identification using intuitionistic fuzzy driven retinex
Jayasurya Ramakrishnan, Sriramakrishnan Pathmanaban, Vinodkumar Arumugam · 2026
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Description
Jayasurya Ramakrishnan, Sriramakrishnan Pathmanaban, and Vinodkumar Arumugam work to lift the quality of microscope images so sickle cell disease can be spotted with more care. The disease is passed in the genes and needs early diagnosis if treatment plans are to work well. Uneven smears, poor focus, uneven light, and bad microscope settings all hide the key shapes in blood images.
Their method, intuitionistic fuzzy driven retinex, joins a fuzzy index part with single scale retinex. One part sharpens local detail and contrast, and the other part evens out light across the whole image. The cleaned up images show clearer sickle cell edges, a better split of cells that lie on top of each other, higher contrast, and less noise. A DenseNet121 classifier trained on these images reaches an accuracy level that stands up well on a Kaggle data set.
Catalog record
| CREATOR | Jayasurya Ramakrishnan, Sriramakrishnan Pathmanaban, Vinodkumar Arumugam |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 60 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |