ItemArticle

Precise cervical cancer cell boundary denoising and segmentation with adaptive wavelet-spectral enhancement

Title
Precise cervical cancer cell boundary denoising and segmentation with adaptive wavelet-spectral enhancement
Creator
Mukku, Lalasa; Lamani, Manjunath Ramanna; Hegde, Lavanya; Mahapurush, Prathima; Mahapurush, Shivanandaswamy
Description
Accurate segmentation of cell nuclei in cervical cytology images is crucial for automated cervical cancer screening, yet existing methods struggle with blurred boundaries, noise-induced degradation, and topologically implausible predictions. The current research proposes Cell-Seg Tool, a novel triplet-branch diffusion AI tool that synergistically integrates three innovations to address these limitations. The Wavelet-Enhanced Contour Refinement Branch employs a learnable multi-scale discrete wavelet transform with adaptive coefficient attention to dynamically enhance boundary features across horizontal, vertical, and diagonal orientations. The Adaptive Spectral Noise Suppression module performs dual-domain processing using DCT-based filtering and uncertainty-guided fusion, coupled with bidirectional anchor semantic feedback to couple cross-branch information. The Topology-Aware Hybrid Loss integrates a focal Tversky loss, a persistent homology loss, a directional boundary loss, a skeleton completeness loss, and a diffusion-noise MSE loss for multi-objective optimization. Comprehensive experiments on multiple datasets demonstrate superior performance, achieving 94.45% Dice coefficient and 19.2% reduction in boundary localization error compared to state-of-the-art methods. Unlike prior work that applies these techniques independently, this work demonstrates that their adaptive, synergistic integration within a diffusion-based framework yields substantial improvements in boundary accuracy and topological correctness. 2026 The Author(s).
Source
International Journal of Advances in Intelligent Informatics;Volume;12;Issue;1;pp.136-164
Date
01-01-2026
Publisher
Universitas Ahmad Dahlan
Subject
Adaptive wavelet-spectral; Cell boundary denoising; Cervical cancer; Cervical cells; Segmentation enhancement
Coverage
Mukku L., CHRIST (Deemed to be University), Bangalore, 560074, India; Lamani M.R., Moodlakatte Institute of Technology, Kundapura, 576217, India; Hegde L., GOVERNMENT SKSJTI, Bangalore, 560001, India; Mahapurush P., SKSVMACET Gadag, India; Mahapurush S., Moodlakatte Institute of Technology, Kundapura, 576217, India
Rights
All Open Access; Gold Open Access; Green Open Access
Relation
ISSN: 24426571;
Format
online
Language
English
Type
Article

Citation

Mukku, Lalasa; Lamani, Manjunath Ramanna; Hegde, Lavanya; Mahapurush, Prathima; Mahapurush, Shivanandaswamy, “Precise cervical cancer cell boundary denoising and segmentation with adaptive wavelet-spectral enhancement,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 19, 2026, https://archives.christuniversity.in/items/show/23441.

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