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When it comes to imaging in medicine, the quality of the picture is vital for precise evaluation particularly breast cancer identification. The full examination of the noise elimination methods used to improve the appearance of breast tumor pictures is presented in this paper. Several popular filtrations were compared and evaluated: standard WF (Wiener Filter), MF (Median Filter), and an improvised Kuan filter. Those filters’ performance is examined using the MSE, PSNR, and SSIM metrics. Our results showed that when it came to MSE, PSNR, and SSIM, the Improvised Kuan filter functioned better than the Wiener and median filtration. The Improvised Kuan filter showed excellent noise mitigation powers by leverage, leading to noticeably better photo quality. It is anticipated that these improved pictures will offer physicians and other healthcare professional’s sharper and additional comprehensive representations, enabling more precise diagnoses and well-informed treatment choices for individuals with breast cancer. From the results obtained improvised Kuan filter gave PSNR of 45.35, SSIM of 0.999, and MSE of 0.000124. The results of the research highlight the value of customized noise reduction methods and highlight the improvised Kuan filter’s effectiveness in improving breast cancer imaging and eventually, enhanced medical results.

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Enhancing Mammogram Image Quality Using Various Noise Removal Techniques and Improvised Kuan Filter

  • 会议论文

  • 发表日期：

    2026年

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  • Tonjam Gunendra Singh,
  • Monita Wahengbam,
  • S. Sivashankar,
  • A. Agnes Pearly,
  • P. Abirami

摘要

When it comes to imaging in medicine, the quality of the picture is vital for precise evaluation particularly breast cancer identification. The full examination of the noise elimination methods used to improve the appearance of breast tumor pictures is presented in this paper. Several popular filtrations were compared and evaluated: standard WF (Wiener Filter), MF (Median Filter), and an improvised Kuan filter. Those filters’ performance is examined using the MSE, PSNR, and SSIM metrics. Our results showed that when it came to MSE, PSNR, and SSIM, the Improvised Kuan filter functioned better than the Wiener and median filtration. The Improvised Kuan filter showed excellent noise mitigation powers by leverage, leading to noticeably better photo quality. It is anticipated that these improved pictures will offer physicians and other healthcare professional’s sharper and additional comprehensive representations, enabling more precise diagnoses and well-informed treatment choices for individuals with breast cancer. From the results obtained improvised Kuan filter gave PSNR of 45.35, SSIM of 0.999, and MSE of 0.000124. The results of the research highlight the value of customized noise reduction methods and highlight the improvised Kuan filter’s effectiveness in improving breast cancer imaging and eventually, enhanced medical results.