Enhanced CT image classification for kidney stones using pruned ConvNeXt and two-tier optimization

The proposed model achieves enhanced detection accuracy and efficiency through the use of Dynamic Channel Pruning and Pufferfish Optimization. This model offers a promising solution for kidney stone detection in CT images.

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Publication Details

Journal
Acta Clinica Belgica
Published
2025-11-02
DOI
https://doi.org/10.1080/17843286.2025.2586626
Primary Topic
Advanced Neural Network Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Enhanced CT image classification for kidney stones using pruned ConvNeXt and two-tier optimization

C. Narmadha, C. Rajanandhini, B. Reuben
Acta Clinica Belgica
Advanced Neural Network Applications
article

Enhanced CT image classification for kidney stones using pruned ConvNeXt and two-tier optimization

C. Narmadha, C. Rajanandhini, B. Reuben
article en

Abstract

The proposed model achieves enhanced detection accuracy and efficiency through the use of Dynamic Channel Pruning and Pufferfish Optimization. This model offers a promising solution for kidney stone detection in CT images.

Acta Clinica BelgicaVol. 80(6)
Periyar Maniammai Institute of Science & Technology (IN)
Openalex Percentile: Top 66%
Advanced Neural Network Applications
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Enhanced CT image classification for kidney stones using pruned ConvNeXt and two-tier optimization — C. Narmadha, C. Rajanandhini, et al. · Acta Clinica Belgica (2025) | TGRS Research Map | TGRS