Ravi ShankerABV-Indian Institute of Information Technology and Management Gwalior | IIITM · DIGITAL IMAGE PROCESSING
Working as Project Linked Scientist at ABV-Indian Institute of Information Technology and Management Gwalior, India
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The automated and accurate detection of brain tumors is challenging for classifying brain Magnetic Resonance (MR) images. The conventional techniques for diagnosing the images are tedious and inefficient in decision making. Therefore, this work proposes an adaptive and non-invasive method for accurately classifying images into pathological and norm...
Brain abnormalities are neurological disorders of the human nervous system that contain biochemical, electrical, and structural changes in the brain and spinal cord. However, such changes produce diverse symptoms like paralysis, amnesia, and muscle weakness. The diagnosis of these abnormalities is crucial for treatment planning in the early stage t...
The segmentation and classification of brain magnetic resonance (MR) images are the crucial and challenging task for radiologists. The conventional methods for analyzing brain images are time-consuming and ineffective in decision-making. Thus, to overcome these limitations, this work proposes an automated and robust computer-aided diagnosis (CAD) s...
Robust segmentation of the brain magnetic resonance (MR) images is extremely important for diagnosing the tissues quantitatively. It is crucial to detect the changes caused by the growth of edema and tumor in healthy tissues for better medical treatment planning. In order to increase the image quality, skull stripping or brain extraction is an esse...
Segmentation of brain tumor from magnetic resonance imaging is a time consuming and critical task due to unpredictable characteristics of tumor tissues. In this paper, we propose a new tissue segmentation algorithm that segments brain MR images into gray matter (GM), white matter (WM), cerebrospinal fluid (CSF), tumor and edema. It is crucial to se...
PCNN Model is widely used because it simulates the working of visual cortex in cats, but parameter setting in PCNN is hefty affair because of manual adjusting of many initial parameters. Through this paper, we present an efficient optimization approach to reducing the parameter setting in original PCNN model by changing the threshold function to mo...
Wavelength division multiplexing allow the multiple channel to transmit the data at high speed at the same instant. For large distance communication, Single mode fiber is preferred over Multimode fiber. Quality factor decreases as data rate and optical fiber length increases. In this proposed work Optisystem 13.0 simulator is used to analyze disper...
1. Study of Morphological changes in an SCA affected patients through image processing and computer vision-based techniques using MR images. 2. Assessment of progressive disorder of degradation of cells for cerebral and cerebellum atrophy using image processing. 3. Comparison of the clinical changes captured by image features among SCA1, SCA2, and SCA12 types. 4. Study of progression of Atrophy. 5. Development of appropriate software for an automated clinical study based on machine learning