Alzheimer’s disease, a progressive neurodegenerative disorder of the brain, is a major cause of death around the globe. Clinical symptoms of the disease appear at later stages, however, modern brain imaging techniques have enabled us to non-invasively visualize the internal structures of the brain and identify structural and functional changes well before time. Early detection of the disease is crucial for the patient, care givers and relatives to cope with the situation as well as for medical practitioners to discover new drugs. A novel image processing based approach is proposed for early identification of Alzheimer’s disease from MRI of the brain. Features used are different tissue densities and size of hippocampus. Seven classification models are used for identification of patients and controls. Results are obtained using image features, genetic features and combination of the both. Image features produced best classification of cases and controls. On the other hand, genetic data can be very useful in predicting the risk of disease. The proposed approach has achieved higher accuracy/specificity/sensitivity values even using smaller feature set.
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Saima Farhan PhD, is working as assistant professor in the Department of Computer Science, Lahore College for Women University, Lahore, Pakistan, since last 10 years. Her research interests include image processing, machine learning and medical image analysis. She has authored two books and many international conference and journal research papers.
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Alzheimer's disease, a progressive neurodegenerative disorder of the brain, is a major cause of death around the globe. Clinical symptoms of the disease appear at later stages, however, modern brain imaging techniques have enabled us to non-invasively visualize the internal structures of the brain and identify structural and functional changes well before time. Early detection of the disease is crucial for the patient, care givers and relatives to cope with the situation as well as for medical practitioners to discover new drugs. A novel image processing based approach is proposed for early identification of Alzheimer's disease from MRI of the brain. Features used are different tissue densities and size of hippocampus. Seven classification models are used for identification of patients and controls. Results are obtained using image features, genetic features and combination of the both. Image features produced best classification of cases and controls. On the other hand, genetic data can be very useful in predicting the risk of disease. The proposed approach has achieved higher accuracy/specificity/sensitivity values even using smaller feature set. 164 pp. Englisch. Seller Inventory # 9783659772177
Seller: moluna, Greven, Germany
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Farhan SaimaSaima Farhan PhD, is working as assistant professor in the Department of Computer Science, Lahore College for Women University, Lahore, Pakistan, since last 10 years. Her research interests include image processing, machi. Seller Inventory # 158605299
Seller: preigu, Osnabrück, Germany
Taschenbuch. Condition: Neu. Alzheimer's Disease Estimation | A Pattern Recognition based Approach using MRI and Genotype Data | Saima Farhan (u. a.) | Taschenbuch | 164 S. | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783659772177 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 104227469
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Alzheimer¿s disease, a progressive neurodegenerative disorder of the brain, is a major cause of death around the globe. Clinical symptoms of the disease appear at later stages, however, modern brain imaging techniques have enabled us to non-invasively visualize the internal structures of the brain and identify structural and functional changes well before time. Early detection of the disease is crucial for the patient, care givers and relatives to cope with the situation as well as for medical practitioners to discover new drugs. A novel image processing based approach is proposed for early identification of Alzheimer¿s disease from MRI of the brain. Features used are different tissue densities and size of hippocampus. Seven classification models are used for identification of patients and controls. Results are obtained using image features, genetic features and combination of the both. Image features produced best classification of cases and controls. On the other hand, genetic data can be very useful in predicting the risk of disease. The proposed approach has achieved higher accuracy/specificity/sensitivity values even using smaller feature set.Books on Demand GmbH, Überseering 33, 22297 Hamburg 164 pp. Englisch. Seller Inventory # 9783659772177
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Alzheimer's disease, a progressive neurodegenerative disorder of the brain, is a major cause of death around the globe. Clinical symptoms of the disease appear at later stages, however, modern brain imaging techniques have enabled us to non-invasively visualize the internal structures of the brain and identify structural and functional changes well before time. Early detection of the disease is crucial for the patient, care givers and relatives to cope with the situation as well as for medical practitioners to discover new drugs. A novel image processing based approach is proposed for early identification of Alzheimer's disease from MRI of the brain. Features used are different tissue densities and size of hippocampus. Seven classification models are used for identification of patients and controls. Results are obtained using image features, genetic features and combination of the both. Image features produced best classification of cases and controls. On the other hand, genetic data can be very useful in predicting the risk of disease. The proposed approach has achieved higher accuracy/specificity/sensitivity values even using smaller feature set. Seller Inventory # 9783659772177