Abstract
Tohoku University has nearly a 30-year-long history of basic and clinical research in molecular imaging using radiopharmaceuticals. This article briefly overviews the various achievements of Tohoku University in the fields of oncology and neuroscience. It is noteworthy that most of the early data regarding oncology diagnosis using positron emission tomography (PET) were produced at the Cyclotron and Radioisotope Center of the university. Also, the center has various academic contributions to the filed of neuroscience. One of its major contributions is molecular imaging of histamine H1 receptors, and recent achievements in this topic are summarized in this paper. The histaminergic neuronal system is associated with various functions such as wakefulness, the sleep-wake cycle, appetite control, learning, memory and emotion. Using [11C]doxepin and PET, various studies have been conducted regarding physiological changes such as aging and pathological changes such as Alzheimers disease, depression, and schizophrenia. In addition, histamine H1 receptor antagonists (antihistamines) are frequently used for the treatment of allergic disorders. These compounds can induce sedative side effects that can cause serious traffic accidents. Objective measurement of the sedative property of antihistamines was started in the early 1980s and was established at Tohoku University using H1 receptor occupancy as an index. In the future, PET will undoubtedly be used more frequently in drug development.
Call for Papers in Thematic Issues
Intelligent Information Retrieval for Multispectral and Hyperspectral Imaging
Multispectral and hyperspectral imaging is an interdisciplinary research area, widely focuses on spectral, spatial, and temporal data. It offers a plethora of opportunities to efficiently analyze the vast area of the earth's surface. However, there are numerous factors such as dimensionality and size of the hyperspectral data, lesser training samples, ...read more
Machine and Deep Learning in Medical Image Diagnosis
Medical Image Processing regards a set of methodologies that have been developed over recent years with the purpose of improving medical image quality, improving medical data visualization, understanding, and assisting medical diagnosis, and so on. The application of machine and deep learning methods in sensing and imaging can potentially have ...read more
Quantum Machine Learning for Medical Data and Imaging
Quantum computing has promised a significant speedup in certain computationally intensive tasks that are intractable on classical computers. Researchers in quantum machine learning, such as those working in computer vision, image processing, biomedical analysis, and related topics, may play an important role in comprehending and working on complicated medical data, ...read more
13