eng Oriental Scientific Publishing Company Biomedical and Pharmacology Journal 0974-6242 2026-03-20 19 1 669 682 10.13005/bpj/3384 69923 article Tamilselvi Rajendran 1 Parisa Beham Mohammed 1 Shanmugapriya 1 Sathiya Pandiya Lakshmi 1 Nandhineeswari 1 Gayathri 1 Department of ECE, Sethu Institute of Technology, kariapatti, Tamil Nadu, India Osteoporosis represents a significant global health issue, marked by diminished bone density and a heightened susceptibility to fractures. Early detection is essential for effective intervention; however, prevailing diagnostic techniques such as Dual-Energy X-ray Absorptiometry (DEXA) are often prohibitively expensive and difficult to access in numerous areas. Although ultrasound-based methods offer a non-invasive and economically viable alternative, their precision is frequently undermined by noise present in the signals. This paper undertakes a comparative examination of both traditional and contemporary signal processing filters (including Low-pass, Median, Wavelet, Kalman, Bilateral, Anisotropic Diffusion and Savitzky-Golay filters) and introduces a groundbreaking hybrid filter that integrates Wavelet Transform, Wiener Filter and Non-Local Means Filter. The hybrid filter proposed here is specifically engineered to maintain essential signal characteristics while effectively mitigating noise, thus rendering it highly suitable for the detection of osteoporosis. The proposed hybrid filter integrates Wavelet Transform, Wiener, and Non-Local Means Filter techniques to enhance signal denoising, achieving superior performance over traditional methods. We evaluate the performance of the proposed filter using a dataset of simulated ultrasound signals, both normal and osteoporotic. The signals are processed using Fourier and Wavelet transforms for feature extraction, and a 1D CNN is employed for classification. The results demonstrate that the hybrid filter outperforms traditional and advanced filters in terms of accuracy, sensitivity, and F1-score, making it a promising tool for clinical applications. https://biomedpharmajournal.org/vol19no1/analysis-of-hybrid-and-benchmark-filters-for-enhanced-noise-removal-in-ultrasound-signals-for-osteoporosis-detection/ 1D CNN Hybrid Filter Non-Local Means Filter Osteoporosis Detection Ultrasound Signal Processing Wavelet Transform