We introduce a new method for analysis of X-ray fluorescence (XRF) spectra based on continuous wavelet transform filters, and the method is applied to the determination of toxic metals in pharmaceutical materials using hand-held XRF spectrometers. The method uses the continuous wavelet transform to filter the signal and noise components of the spectrum. We present a limit test that compares the wavelet domain signal-to-noise ratios at the energies of the elements of interest to an empirically determined signal-to-noise decision threshold. The limit test is advantageous because it does not require the user to measure calibration samples prior to measurement, though system suitability tests are still recommended. The limit test was evaluated in a collaborative study that involved five different hand-held XRF spectrometers used by multiple analysts in six separate laboratories across the United States. In total, more than 1200 measurements were performed. The detection limits estimated for arsenic, lead, mercury, and chromium were 8, 14, 20, and 150 μg/g, respectively.
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Med Image Anal
January 2025
Department of Electrical and Computer Engineering, College of Information and Communication Engineering, Sungkyunkwan University, Suwon, 440-746, South Korea. Electronic address:
This study introduces HCC-Net, a novel wavelet-based approach for the accurate diagnosis of hepatocellular carcinoma (HCC) from abdominal ultrasound (US) images using artificial neural networks. The HCC-Net integrates the discrete wavelet transform (DWT) to decompose US images into four sub-band images, a lesion detector for hierarchical lesion localization, and a pattern-augmented classifier for generating pattern-enhanced lesion images and subsequent classification. The lesion detection uses a hierarchical coarse-to-fine approach to minimize missed lesions.
View Article and Find Full Text PDFJ Zhejiang Univ Sci B
December 2024
Center for Cognition and Brain Disorders / Department of Neurology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou 311121, China.
White-matter tracts play a pivotal role in transmitting sensory and motor information, facilitating interhemispheric communication and integrating different brain regions. Meanwhile, sensorimotor disturbance is a common symptom in patients with major depressive disorder (MDD). However, the role of aberrant sensorimotor white-matter system in MDD remains largely unknown.
View Article and Find Full Text PDFComput Methods Programs Biomed
January 2025
Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education, Nanjing, China; School of Computer Science and Engineering, Southeast University, Nanjing, China.
Purpose: Dual-energy computed tomography (DECT) enables the differentiation of different materials. Additionally, DECT images consist of multiple scans of the same sample, revealing information similarity within the energy domain. To leverage this information similarity and address safety concerns related to excessive radiation exposure in DECT imaging, sparse view DECT imaging is proposed as a solution.
View Article and Find Full Text PDFMath Biosci Eng
December 2024
School of Information Engineering, Nantong Institute of Technology, Nantong 226002, Jiangsu, China.
As an essential component of mechanical systems, bearing fault diagnosis is crucial to ensure the safe operation of the equipment. However, vibration data from bearings often exhibit non-stationary and nonlinear features, which complicates fault diagnosis. To address this challenge, this paper introduces a novel multi-scale time-frequency and statistical features fusion model (MTSF-FM).
View Article and Find Full Text PDFBiomed Phys Eng Express
January 2025
Electronics and Communication Engineering, Rajiv Gandhi University, Rono Hills, Doimukh, ITANAGAR, Itanagar, Arunachal Pradesh, 791112, INDIA.
Accurate detection of cardiac arrhythmias is crucial for preventing premature deaths. The current study employs a dual-stage Discrete Wavelet Transform (DWT) and a median filter to eliminate noise from ECG signals. Subsequently, ECG signals are segmented, and QRS regions are extracted for further preprocessing.
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