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September 28, 2025Aptisi Transactions On Technopreneurship (ATT)Open Access

Technopreneurial Filtering Technique for Speckle Noise Reduction in Ultrasound Imaging of Polycystic Ovary Syndrome

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Authors

PPPratibha PandeySCSumit ChaudharyXNXin Nie

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Overview

New model enhances image quality in ultrasound imaging of PCOS by reducing speckle noise, indicating potential for better diagnosis.

Key Points

  • The attention-based autoencoder significantly improves image quality, facilitating more accurate diagnosis of PCOS.
  • Testing on a dataset showed improvements with PSNR values of 31.33, 34.25, and 36.23 at different noise levels.
  • Conventional methods suffer from preserving details while reducing noise, unlike the proposed AAE approach.
  • The findings may lead to scalable AI-driven diagnostic tools for PCOS within a technopreneurship incubator model.

Cite This Study

Pandey et al. (2025) studied this question.

synapsesocial.com/papers/68d913ab4ddcf71ba560bc40https://doi.org/10.34306/att.v7i3.767
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Speckle Noise Reduction in Ultrasound Images using Denoising Auto-encoder with Skip Connection2024
  2. 2Speckle Noise Reduction in Ultrasound Images using Denoising Auto-encoder with Skip connection2024 · 1 citations
  3. 3Denoising of Medical Ultrasound Images Using Variational Autoencoders Guided by Attention Mechanisms2026
  4. 4Adaptive Archimedes optimization algorithm trained deep learning for polycystic ovary syndrome detection using ultrasound image2025
  5. 5A multimodal feature fusion with deep representation learning approach for polycystic ovary syndrome diagnosis using ultrasound images2026 · 2 citations