Plasma Assisted Generation of Micro- and Nanoparticles

In this research, the peculiarities of micro- and nanoparticles generation are considered. Two techniques of micro- and nanoparticles' formation using electric arc and underwater discharge plasma sources are proposed. Molybdenum oxide crystals were deposited on side surface of the bottom electrode (anode) of the free-burning discharge between metallic molybdenum electrodes. Friable layer of MoO3, which consists of variously oriented transparent prisms and platelets (up to few hundreds of $mu;m in size), was formed by vapor deposition around the electrode. In the second technique, plasma of the underwater electric spark discharges between metal granules was used to obtain stable colloidal solutions with nanoparticles of 20-100 nm sizes

Etude d'un arc impulsionnel immergé à l'aide de deux dispositifs expérimentaux

International audienc

Bridging the Gap Between AI and Healthcare Sides: Towards Developing Clinically Relevant AI-Powered Diagnosis Systems

Despite the success of Convolutional Neural Network-based Computer-Aided Diagnosis research, its clinical applications remain challenging. Accordingly, developing medical Artificial Intelligence (AI) fitting into a clinical environment requires identifying/bridging the gap between AI and Healthcare sides. Since the biggest problem in Medical Imaging lies in data paucity, confirming the clinical relevance for diagnosis of research-proven image augmentation techniques is essential. Therefore, we hold a clinically valuable AI-envisioning workshop among Japanese Medical Imaging experts, physicians, and generalists in Healthcare/Informatics. Then, a questionnaire survey for physicians evaluates our pathology-aware Generative Adversarial Network (GAN)-based image augmentation projects in terms of Data Augmentation and physician training. The workshop reveals the intrinsic gap between AI/Healthcare sides and solutions on Why (i.e., clinical significance/interpretation) and How (i.e., data acquisition, commercial deployment, and safety/feeling safe). This analysis confirms our pathology-aware GANs’ clinical relevance as a clinical decision support system and non-expert physician training tool. Our findings would play a key role in connecting inter-disciplinary research and clinical applications, not limited to the Japanese medical context and pathology-aware GANs