Predictive projection in color fundus-retail images for detection of Alzheimer’s disease

Abstract

Alzheimer’s disease is a prominent abnormality found in population above 50-60 years. This disease is prevalent in elderly resulting in steady decline of memories, functioning of social and motor abilities, cognition. This abnormality is identified by sedimentation of various types of proteins in brain of a human being. The reports are manually graded in conventional methods of treatments. It is also believed that manual analysis provides the exact measure of progress/regress of the disease. This research has been a primary case in medical history and it has been subjected to many investigations in recent decades. The prevalence of degradations has been identified in neuron networks of retina too. From the results investigated and modules derived by many researchers state, that there are distinct changes in parameters of human retina of Alzheimer’s disease affected patients. Since these altered parameters could be utilized for detection of this disease, neuropathology advocated the usage of biomarkers to observe the diseases. Comparatively, these methods of monitoring retinal fundus images have proven to be non-invasive to the other methods, since retinal images provide a transplant medium for the studies. Managing this Alzheimer’s disease has become easier with retinal in ageing technology and usual testing methods. All these methods in turn improved the lifestyle of AD infected patients. They also do not have any invasive techniques, which added to the suffering of patients. Treatment should be planned according to have a better diagnosis. As the proverb says, ‘Prevention is better than cure’, early treatments reduce the prolonged effects of a disease. The treatment and diagnosis plan should be reliable and trustworthy when being cost efficient. When the disease is at its early phases, a systematic approach could be used to profile the parameters of humankind. Multiple image processing techniques are implemented in medical industry to simplify the practice. This paper proposes an innovative technique of modeling color fundus images into axis to determine the progress of neurological degradations. This approach segments the retinal images for grading monitoring and diagnosing Alzheimer’s disease.