Journal Articles

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/19884

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Subject: search.filters.subject.Image sampling

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    Optimization of countour based template matching using GPGPU based hexagonal framework
    (Machine Intelligence Research (MIR) Labs contact@mirlabs.org, 2015) Bhagya, M.; Tripathi, S.; Santhi Thilagam, P.
    This paper presents a technique to optimize contour based template matching by using general purpose computation on graphics processing units (GPGPU). Contour based template matching requires edge detection and searching for presence of a template in an entire image, real time implementation of which is not trivial. Using the proposed solution, we could achieve an implementation fast enough to process a standard video (640x480) in real time with sufficient accuracy.
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    Analyzing data incompleteness for MRI Data for quality enhancement
    (Institute of Electrical and Electronics Engineers Inc., 2024) Shanbhag, S.; Raju, S.; Gurupur, V.P.; Kamath, S.S.; Kandala, R.N.V.P.S.; Trader, A.E.; Lal, S.
    Magnetic resonance imaging (MRI) is a powerful medical imaging technique widely used for diagnosing various conditions because it provides detailed images of internal structures within the body. However, like any imaging modality, MRI images can be susceptible to artifacts that may arise from various sources, including hardware imperfections, patient motion, and image acquisition techniques. Detecting and mitigating these artifacts are crucial steps in ensuring MRI scans' reliability and clinical utility. In this paper, we present algorithms specifically designed to address the challenges of undersampling and motion artifacts in MR images. Our approach involves leveraging advanced image processing techniques, including line detection algorithms for undersampling detection and blur parameter estimation for motion artifact analysis. By accurately identifying and quantifying these artifacts, our algorithms aim to improve MRI data's overall quality and completeness, ultimately enhancing diagnostic accuracy and patient care. © 2024 The Authors.