Suhas Gajre

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Osteoarthritis (OA) of knee is the most commonly occurring non-fatal irreversible disease, mainly in the elderly population and particularly in female. Various invasive and non-invasive methods are reported for the diagnosis of this articular cartilage pathology. Well known techniques such as X-ray, computed tomography, magnetic resonance imaging,(More)
Discrete wavelet transforms are extensively preferred in biomedical signal processing for denoising, feature extraction, and compression. This paper presents a new denoising method based on the modeling of discrete wavelet coefficients of ECG in selected sub-bands with Kernel density estimation. The modeling provides a statistical distribution of(More)
Linear Predictive coding (LPC) is extensively used for analysis and compression of speech signal whereas the Discrete Wavelet Transform is widely preferred for electrocardiogram (ECG) compression. In this paper, we present LPC and wavelet based method to encode ECG signals. The compression algorithm has been evaluated with the MIT-BIH Arrhythmia Database,(More)
The electrical activity of muscles is usually modeled using Gaussian probability distribution function. Such assumption is not always true, because real-life muscle noise has impulse character as well. Adaptive threshold technique is one important step in the detection of QRS Complexes. However, presence of impulse noise may trigger false positives. The(More)
Knee osteoarthritis (OA) is a degenerating disorder that leads to pain, disability and dependence. Although significant numbers of elderly people are affected by this irreversible damage, not many non-invasive methods have been found that can detect onset of OA. The traditional x-ray has the disadvantage of detecting a problem only after many changes have(More)
The discrete wavelet transform has great capability to analyze the temporal and spectral properties of non stationary signal like electrocardiogram (ECG). In this paper, we developed and evaluated a robust algorithm using multiresolution analysis based on the discrete wavelet transform (DWT) for twelve-lead ECG temporal feature extraction. The study, with(More)
Knee Osteoarthritis (OA) is a most prevalent joint disease that can be diagnosed by measuring physiology and morphology of knee joint organs using Magnetic Resonance Imaging (MRI). Measurement of morphological changes in the knee joint organs is a highly challenging task as it requires interpretation and analysis from MR images acquired using different MR(More)
This paper presents an analog integrated circuit implementation of a cortical neuron model that produces different spiking patterns with biological plausible spike shape. The circuit mimics the behaviour of known classes of cortical neurons: regular spiking (RS), fast spiking (FS) and chattering (CH). Operation of circuit and its simulation results for 180(More)
Most medical images suffer from inadequate contrast and brightness, which leads to blurred or weak edges (low contrast) between adjacent tissues resulting in poor segmentation and errors in classification of tissues. Thus, contrast enhancement to improve visual information is extremely important in the development of computational approaches for obtaining(More)
Knee osteoarthritis (OA) progression can be monitored by measuring changes in the subchondral bone structure such as area and shape from MR images as an imaging biomarker. However, measurements of these minute changes are highly dependent on the accurate segmentation of bone tissue from MR images and it is challenging task due to the complex tissue(More)