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AI / informaticsRadiological physics and technology · 2026

Content-based retrieval of fundus images and diabetic retinopathy detection using variants of local texture features.

Arpita Santra, Imtiyaz Ahmad, Vibhav Prakash Singh

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OphthalmologyAI / informatics

Differential Evolution feature selection gave the most precise retinal image retrieval.

Content-based retrieval of fundus images and diabetic retinopathy detection using variants of local texture features.

Arpita Santra … Vibhav Prakash Singh

Radiological physics and technology · 2026

Background

Content-based retinal image analysis plays a crucial role in the early diagnosis of ocular diseases.

90.67%

Results

90.67%

in a top-10 image search, this share were truly matching, or relevant

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A comparative analysis between preprocessed and raw images highlights the impact of preprocessing techniques on performance.

This hybrid approach enhances the system's capability to handle diverse retinal image variations, leading to improved retrieval accuracy and robustness.

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Conclusion

This research contributes to precision medicine and healthcare innovation by advancing ML-driven retinal image analysis.

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Content-based retrieval of fundus images and diabetic retinopathy detection using variants of local texture features.

Differential Evolution feature selection gave the most precise retinal image retrieval.

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