Recently, the Arterial Network learned that Royal Philips of the Netherlands announced that China’s first “Philips Nebula Medical Imaging Artificial Intelligence Platform” landed at the Bethune First Hospital of Jilin University (hereinafter referred to as “Ji Da Yi”), and assisted radiologists through intelligent image post-processing. Patients provide accurate diagnosis and support for clinical research and application transformation. Based on the platform, the two sides will promote the research and transformation of AI images in specific clinical scenarios through close clinical research cooperation.

The First Hospital of Bethune, Jilin University is a large-scale comprehensive tertiary hospital with medical , teaching, scientific research, prevention, health care and rehabilitation. In 2016, in the list of Chinese hospitals in Fudan University, the hospital ranked 44th in the country. In recent years, due to the increasing number of hospital patients, the work pressure of radiologists has become more serious. In order to improve efficiency, Professor Hua Shucheng, Dean of Bethune First Hospital of Jilin University, decided to cooperate with enterprises to explore and try artificial intelligence.

For this cooperation, Dean Hua said: "Precise medicine, image first. Artificial intelligence technology can fully exploit the value of medical image big data. Currently, the country is vigorously promoting medical big data applications. In this context, hospitals are also We are actively preparing. The radiology department of our hospital is committed to making use of the advantages of many cases and rich diseases in our hospital, and innovating the combination of medical and industrial transformation, so as to better achieve data from clinical and clinical. The landing of 'Philips Nebula Medical Imaging Artificial Intelligence Platform' will surely become a powerful driving force for the development of image big data and artificial intelligence in our hospital."

There are many companies engaged in AI+ medical care in China, and it is not easy to choose the most appropriate one. Professor Wang Haifeng, the vice president of Bethune First Hospital of Jilin University, thinks it is not easy.

"We will first look at the characteristics of this company, and at the same time we will look at the company's products and the company's development prospects. There are many companies doing big data and artificial intelligence at home and abroad, but the company we ultimately choose must be a lot of history, and at the same time The strength of its research team is strong enough to understand the hospital's clinical research, diagnosis, and application, and it is more practical." Under this selection criteria, the hospital finally cooperated with Philips.

According to President Wang, the First Hospital of Bethune, Jilin University has a large number of patients and diseases. Using Philips' big data collection and collection, data of a certain disease can be collected in a short time.

Dean Wang believes that as a manager of a hospital, you cannot simply think about problems from the perspective of a department. Think from a hospital, a province, or a higher level. As the current academic status of Bethune First Hospital of Jilin University is relatively high, as a large-scale public hospital, it should assume corresponding social responsibilities, radiate high-quality medical resources to the medical association, and help grassroots hospitals integrate internal data resources. Thereby achieving a two-way upgrade.

Specifically, the hospital helps the artificial intelligence products to mature through the operation and coordination of the artificial intelligence system by professors and experts, thereby radiating downwards and assisting the doctors in the lower-level hospitals in making clinical decisions. Through the artificial intelligence platform, it can also save the time and effort of the superior hospital and target the critically ill patients for treatment. In this way, it can not only improve the medical services of lower-level hospitals, improve the quality of medical care, but also enable the higher-level hospitals to form a leading and leading role.

The "Philips Nebula Medical Imaging Artificial Intelligence Platform" in the mouth of President Wang is the key product of this cooperation. It is reported that the platform has obtained the FDA and CFDA dual certification, consisting of "Philips Nebula 3D Image Post Processing Platform (IntelliSpace Portal, hereinafter referred to as ISP)" and "Philippine Nebula Discovery Platform (IntelliSpace Discovery, hereinafter referred to as ISD)) .

As a clinical imaging diagnostic platform, ISP covers multiple clinical fields of radiology, including cardiology, oncology (liver, lung, breast, prostate, etc.) and neurology. There are more than 80 applications in it, enabling different brands, Image fusion of different types of imaging equipment, providing advanced visualization of multimodal images and disease image feature mining, longitudinal tracking of lesions and advanced feature description functions, assisting clinicians to make rapid and accurate clinical diagnosis decisions based on images, planning Individualized treatment options to follow up on disease treatment.

As a scientific research platform, ISD adopts an open source architecture and is equipped with a wealth of algorithm components, an open artificial intelligence platform, a programming platform, and a database management system. It includes three research modules: tumor, heart and nerve. It can support hospitals and third-party platforms to develop and quickly validate clinical research algorithms, help doctors to easily integrate their own algorithms or third-party clinical research applications, and seamlessly integrate into hospital work and research. The process transforms its research into meaningful clinical applications.

For the "Philips Nebula Medical Imaging Artificial Intelligence Platform", Mr. He Guowei, CEO of Lipu Greater China, said: "The Philips Nebula Medical Imaging Artificial Intelligence Platform is one of Philips' innovative foundations for creating value for precision medicine based on AI technology. Our goal is to closely integrate the world's leading innovation resources with the local clinical situation from the pain points and needs of China's health care system, and actively build a 'local ecosystem' that combines 'production, learning and research' to help China achieve AI+. Medical 's 'breakthrough innovation, promoting the homogenization of quality medical resources."

The pulmonary nodule assessment system is a clinical application of computer aided technology to help doctors quickly detect small pulmonary nodules in the "Philips Nebula Workstation" integrated lung disease solution.

In the latest v9 release, the Philips team upgraded the detection algorithm for small pulmonary nodules and added machine learning algorithms. It has been confirmed in the literature that the algorithm can obtain an error rate of less than 1% in the detection of nodule size from 4mm to 30mm, and the stability of the detection algorithm is much higher than that of the radiologist, thus achieving the second pair of radiologists. Eyes, make doctors more confident in clinical decision-making.

At the same time, detailed quantitative information about the nodule will also be presented in the form of a structured report. These include nodule volume doubling time, volume growth percentage, effective diameter, and statistical information of HU values. Nebula workstation's proprietary one-click nodule volume extraction and high-level structured reports enable rapid circulation of paper or digital reports.

As a comprehensive solution for lung disease, Nebula Workstation helps healthcare professionals manage the full cycle of patient disease through a range of different applications for lung disease:

For example, in the pulmonary vascular assessment system, Philips uses a fully automated analytical tool to help doctors discover vascular embolism in adult lungs; in patients with chronic obstructive pulmonary disease, Philips measures and displays through a semi-automated tool (CT COPD) The severity of the condition of COPD patients; in the application of CT Calcium in patients, in the application of CT Calcium, Philips made a one-click assessment of disease risk through 3D segmentation and quantification of pulmonary vascular calcification information.

When these diagnostics are over, the multimodal tumor tracking system provided by Nebula Workstation provides additional tools to help clinicians monitor disease progression. Among them, the sensitivity analysis of tumors to drugs and the tracking of changes in individual tumors. In the one-stop lung disease solution of the Nebula workstation, Philips is able to provide services for detection, diagnosis and even treatment management throughout the patient's entire disease.

IntelliSpace Discovery (ISD) is an enterprise-level solution for research and a medical imaging platform technology with a forward-looking artificial intelligence framework.

ISD can not only help scientific research institutions to quickly develop the required algorithms and products, but also mobilize third-party medical technology companies to carry out platform construction and joint innovation, and realize the rapid transformation of scientific research results into clinical applications.

The platform consists of two parts: software and hardware. The software is divided into tumor, cardiovascular and neuroscience research kits according to the type of disease. The hardware component uses NVIDIA's next-generation artificial intelligence data center-level dedicated processing accelerator to increase the performance of the artificial intelligence training framework by a factor of five. Such a configuration will not only accelerate the development of the algorithm, but also improve the overall efficiency of clinical applications.

As hospitals pay more and more attention to academic research, Philips will also provide professional artificial intelligence and technical consulting services in medical image processing based on ISD platform to help research institutions break through scientific research bottlenecks and achieve higher academic attainments.

In addition, Philips scientists have also collaborated with Pasch Medical in clinical collaboration to integrate nasopharyngeal carcinoma radiotherapy target planning algorithms into ISD for clinical process integration. The algorithm not only adopts advanced image segmentation and enhancement techniques, but also uses Markov artificial neural network algorithm to improve the accuracy of target prediction. The original 4-hour radiotherapy manual planning time is shortened to within a few minutes, and the accuracy can be Achieve the planning level of a senior radiologist.

Radiomics is one of the hotspots in the field of medical imaging research. Its concept was first proposed by Dutch scholar Lambin in 2012.

The idea of ​​imaging omics is derived from tumor heterogeneity. The spatial and temporal heterogeneity of solid tumors at the gene, protein, cell, microenvironment, tissue and organ levels limits the accuracy and representativeness of invasive assays such as pathology and molecular science. Medical imaging can comprehensively and non-invasively and quantitatively observe the overall morphology of the tumor, and monitor the development process and treatment response of the tumor at any time, thus providing a reliable solution for tumor heterogeneity.

The deep meaning of image omics emphasizes the high-throughput extraction of large amounts of image information from images (CT, MRI, PET, etc.) to achieve tumor segmentation, feature extraction and model building. Through deeper mining, prediction and analysis of massive image data information to assist physicians in making the most accurate diagnosis.

Image omics can also be intuitively understood as the conversion of visual image information into deep features for quantitative research. With the gradual popularization of imaging omics, the research on the benign and malignant identification and grading of tumors and prognosis has received great attention.

The Philips Radiomics platform developed by the Philips Clinical Sciences team is the first in the industry with two modules: image omics feature calculation and machine learning feature analysis. The platform can make the complicated operation process of image omics research convenient and intelligent, and provide a more friendly operation interface for doctors.

The Image Tubing Feature Calculation Suite includes a two-dimensional data manipulation window and a three-dimensional data display window. The Machine Learning Feature Analysis Suite is used to analyze the calculated high dimensional omics features. The established model will eventually be tested on the test set to evaluate the effects of each model and finally select the optimal machine learning model.

At present, the Philips clinical science team has used the platform to include medical research on tumors and nerves in more than 10 top three hospitals including Ruijin Hospital, Concord Hospital, Shengjing Hospital, Tiantan Hospital and Huaxi Hospital, covering CT/MR/PET, etc. A variety of imaging modalities.

For the future of a series of image artificial intelligence platforms, experts from Bethune First Hospital of Jilin University and Philips experts have a common view: artificial intelligence is opening a new era of transformation.

When humans turn their massive data into meaningful insights, intelligent solutions will provide us with active, accurate and personalized care that promotes equal quality health care for all. However, artificial intelligence can never completely replace doctors, nurses, or caregivers, because only the “human” experience and wisdom can train “smart artificial intelligence”. Only "people" themselves can provide "temperature" care for "people."

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