Ultrasound diagnostic device that can display and send with a tablet
Starting with manufacturing and logistics, the applications of AI・IoT are expanding into all industry fields for optimization and to realize a convenient and secure life. There are also big expectations in the medical field and is being used for the collection, storage, sharing, and analysis of health data.
Fujikin, which is mainly engaged in the development and manufacturing of valve equipment, has been developing medical equipment and systems in the IoT era in order to meet the needs of the rapidly growing aging society, and has developed the revolutionary portable ultrasound diagnostic device "MUS Series."
This series can do image diagnosis by connecting it to an Android tablet or Windows computer※1, and if you send image data using a communication line, you can receive advice from external specialist and veteran doctors. Furthermore, the main body is a lightweight 110g for the 7.5MHz linear type (surface use) and 130g for the 5MHz convex type (deep use), and since it can receive power from a USB port connection, mains power or a dedicated power supply is not required.
In addition to doctor's visits in the hospital and home healthcare, it contributes to a quick and accurate diagnosis in emergencies by sending iamges from the scene of the accident. Of course the images are high-definition and operation is simple. Since it is easy to introduce with its small size, it has received high praise from everywhere as a diagnostic device that can easily realize IoT medical care.
※1 Please use in combination with specified computer models. Please inquire about models.
It is not possible to use it with any computer that is commercially available.
Beautifully quick medical image network system
Together with the above-mentioned ultrasound diagnostic device, the "medical image network system" aims to bring IoT to the medical care field.
In recent years, image diagnosis methods have become further advanced and diversified, such as computer tomography equipment "CT" which uses X-ray, "MRI" which uses magnetism to examine inside the body, "PET" which mainly scans for tumors with special medicine, and "CR" digital X-ray equipment.
This medical image network system can consolidate and store these images, share them using an existing internet environment and cloud system, and furthermore it can coordinate with other systems such as electronic medical records. Filed images can be quickly displayed as necessary, and gradation adjustment, zooming, and comparison display with past images can be performed. Its excellent functionality is also shown in its ability to do radiogram interpretation remotely or real time conferencing with a video call.
Also currently, the need for image diagnosis is expanding, but since there is a severe shortage of medical specialists who can read the images, countries all over the world are continuing to develop image diagnosis systems with AI. It is said that its ability has risen to the extent where it can detect small lesions which can be overlooked in difficult cases even by medical specialists, and the connection between the medical image network system and AI is expected to contribute to the realization of advanced and efficient medical care which is required in an ultra aging society.
