20 Kasım 2019 Çarşamba

Hologram Microscope to Facilitate Asthma Diagnosis in Children


A new hologram microscope has been developed which can be used to detect asthma, which is very common in children, before and faster.

Young children are more susceptible to disease than we are, and it is not always easy to diagnose a disease that occurs in them. Tests such as the standard lung function test used to detect asthma cannot be applied to children under certain age. A new blood analyzer can deliver results in less than 2 hours.

This device, a kind of holographic microscope, was developed by the Fraunhofer Marine Biotechnology and Cell Technologies Research Institute of Germany. Pattern imaging and visualization company Raytrix also supported the research. The research was sponsored by the partly state-funded KillAsthma project.


Users start the test by dropping a drop of the patient's blood into the microfluidic cartridge. White blood cells in this example are added to a substance that triggers shortness of breath. After loading, the cartridge is attached to the microscope and the image of 3000 cells is magnified and displayed in three dimensions thanks to the integrated LED and CMOS sensors.

The device was trained using blood samples from persons diagnosed by conventional methods. Thus, the diagnosis can be made with the help of a computer. Although both healthy and sick cells react to the substance that triggers the disease, the response rate drops considerably when it comes to the cells of asthmatics.

After about 90 minutes of monitoring and analysis, the software can accurately diagnose whether the person has asthma. The potential uses of the newly developed technology are not limited to this.

             Dr. Fraunhofer. Daniel Rapoport, methods can be used in the diagnosis of other diseases, he said. He said that immunity and chronic dyspnoea such as Crohn's disease and ulcerated tissues and rheumatism can also be discovered. Detection of these diseases by traditional methods requires a long and difficult test process.


1 Kasım 2019 Cuma

Google Engineers Developed Artificial Intelligence Which Determine Better Than Human, In Lung Disorders


Google, one of the leading companies in the healthcare field of artificial intelligence (AI) and machine learning technology, has collaborated with the Indian hospital chain Apollo Hospitals to develop an artificial intelligence algorithm that analyzes chest X-ray images.

Artificial intelligence (AI), which gives life to many sectors from smart phone to automotive, from military to health, has the potential to overcome many obstacles in front of humanity. One of the companies that are aware of this potential, Google has added a new one to its studies in artificial intelligence. The US technology giant has developed an artificial intelligence algorithm to detect four important findings in people's chest X-rays.

Designed by Google researchers, the model can detect four major lung disorders: pneumothorax, mass, fracture, and opacity. According to research published in the world-famous science journal Nature, the AI algorithm, which is trained using thousands of x-ray images, performs at the radiologist level.


More than 600,000 X-rays were obtained from the India-based hospital chain Apollo Hospitals, which was also supported by Google's umbrella company, Alphabet's artificial intelligence initiative DeepMind. Researchers developed a text-based system using radiology reports associated with each X-ray, and then analyzed more than 560,000 images from the data set provided by Apollo Hospitals.

Google researchers, the artificial intelligence algorithm they developed, doctors can easily see the x-ray images can be detected quickly, he says. Stating that the models determine the findings frequently missed by radiologists, the company said that in some cases, doctors made much better detection than artificial intelligence. Therefore, researchers expressed the need to develop models combining the skills of both AI systems and doctors, and stated that AI applications have tremendous potential in medical image interpretation.