RTDFluxgate magnetometers for detecting iron accumulation in the brain Medical research has made a significant and ongoing effort into improving the quality of human life in all its aspects; in particular, it is committed to understanding and containing the pathological effects associated with the onset of neurodegenerative diseases which, at the moment, remain incurable. Just to mention, Parkinsonu0027s and Alzheimeru0027s diseases are clear examples of these pathologies 1. It is important to iterate that early diagnosis is believed to be crucial in this research activity; in fact, monitoring the alteration of an element, recognized as strictly correlated to the disease, is essential to reduce the progression of the disease itself 2. It is, of course, important to note that these pathologies are strongly disabling, and in detail in the case of Alzheimeru0027s disease, the patient is deprived not only of his memory but also of his daily habits. Typically, the elderly over 65 are susceptible; nevertheless, there are earlier forms that lead to an accelerated demise of nerve cells 3. A schematization of the process is shown in Fig. 1.

Alzheimers Disease Diagnosis Using Enhanced Inception Network Based on Brain Magnetic Resonance Image An estimated 24 million people worldwide have dementia, the majority of whom are thought to have Alzheimeru0027s disease(AD). Nowadays, Alzheimeru0027s disease represents a significant public health concern and has been identified as a research priority. Most unfortunately, there is little chance of a cure for Alzheimeru0027s disease, and the disease is difficult to detect before the dominant characteristics such as memory loss are manifested. Therefore, the diagnosis of Alzheimeru0027s disease has become an urgent problem today. Studies have shown that mild cognitive impairment(MCI) is a state between Alzheimeru0027s disease and normal, and the chance of it turning into Alzheimeru0027s disease is high. Therefore, if machines can automatically learn the characteristics of three kinds of human brain magnetic resonance(MR) images through deep learning, and help doctors to diagnose patients with mild cognitive impairment or Alzheimeru0027s disease accurately, it will be beneficial for the early diagnosis of Alzheimeru0027s disease. In this paper, we improve the Inception(V3) neural network and further test the effectiveness of the enhanced network based on the international Alzheimeru0027s disease data set, which consists of brain magnetic resonance images. The results show that the average accuracy of our approach can reach 85.7%.