SANDEEP CS
@jawaharlalcolleges.com
Associate Professor, Dept. of Electronics and Communication Engineering
JAWAHARLAL COLLEGE OF ENGINEERING AND TECHNOLOGY
RESEARCH, TEACHING, or OTHER INTERESTS
Biomedical Engineering, Electrical and Electronic Engineering, Multidisciplinary
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
C S Sandeep, A Sukesh Kumar, K Mahadevan, and P Manoj
IEEE
Alzheimer disease (AD) is the senile type of dementia as well as a degenerative condition of the brain. AD causes more problems for the aged population after 65 years. Some significant studies made on AD recommends that the neuronal degeneration affecting the brain will also have a tendency to affect the eye. The existing methods are still unable for a definite prediction of the disease at an earlier stage. Therefore, a new efficient method has to be developed to predict the disease at an earlier stage so that necessary treatments can be done to the patients effectively. There are clinical tests, neuropsychological tests and imaging methods for the diagnosis of disease. From these, imaging methods can be used for AD diagnosis. The most important non-invasive imaging methods are Magnetic Resonance Imaging (MRI) and Optical Coherence Tomography (OCT). In this research, we have used images from the OCT device for the early prediction of Alzheimer's type of Dementia. Also, a new technique using Discrete Wavelet Networks (DWNs) named as Marr-Morlet Discrete Wavelet Networks (MMDWNs) for the feature extraction of OCT images has been proposed. This feature extraction process can be used for the early prediction of AD with OCT images. This method provides reliable and validated results for OCT images.
P. G. Prageeth, A. Sukesh Kumar, C. S. Sandeep, and R. S. Jeena
Springer International Publishing
C. S. Sandeep, A. Sukesh Kumar, K. Mahadevan, and P. Manoj
Springer International Publishing
C S Sandeep, A Sukesh Kumar, K Mahadevan, and P Manoj
IEEE
Alzheimer's disease (AD) is the most common form of senile dementia affecting the growing aging population. Clinically, it was proved that there is a progressive decline in cognition, memory, and social functioning due to deposition of different types of protein in the brain. Traditional decision making systems are more manual in nature and ultimate conclusion in terms of exact prognosis is remote. Recently, under certain investigations neurological degradation occurs in the retina of the eye as well as the brain. Also it is clearly investigated that are some parameter changes on the retina of the eye of the AD patients. Therefore eye provides a transparent medium to neuropathology which initiated the development of ocular biomarkers for AD. Retinal imaging and visual testing potentially improves disease management and quality of life for AD patients as they are non invasive methods. Any disease modifying treatments which are developed are most possibly to be achieving success if initiated early in the process, and this needs that we tend to develop reliable, validated and economical ways to diagnose AD. Profiling of human body parameter using computers can be utilized for the early prognosis of AD. There are several imaging techniques used in clinical practice for the prognosis of Alzheimer's type pathology. In this paper we have focused on the fundus imaging, a type of retinal imaging that can be used for the early prognosis of AD. For that we have proposed a new scheme based on Fixed-Grid Wavelet Networks (FGWN) for the segmentation of fundus retinal images that can be used for diagnosing AD.
C.S. Sandeep, Sukesh A. Kumar, and M.J. Susanth
IEEE
Alzheimer's disease (AD) is common form of senile dementia. There are several causes for the disease. Any disease — modifying treatments which are developed are most likely to be successful if initiated early in the process, and this requires that we develop reliable, validated and economical ways to diagnose Alzheimer's-type pathology. However, despite comprehensive searches, no single test has shown adequate sensitivity and specificity, and it is likely that a combination will be needed. In this case, the use of advanced biomedical engineering technology will definitely helpful for making diagnosis. Profiling of human body parameter using computers can be utilized for the early diagnosis of Alzheimer's disease. There are several imaging techniques used in clinical practice for the diagnosis of Alzheimer's — type pathology. Apart from above, before going into the major clinical tests and imaging modalities, our aim to develop and implement a Cognitive Test tool to examine the patients cognitive function for the early diagnosis of AD. By this mental state examination, a physician can screen the stage of the disease and store the test results for future purposes. The implementation has been done on the different patients having dementia of Alzheimer's type, can be used as a medical aid as it saves time than the conventional method.