KEYWORDS: Picture Archiving and Communication System, 3D modeling, Visualization, Visual process modeling, Artificial intelligence, Telecommunications, 3D visualizations, Data modeling, Image processing, 3D image processing
This paper proposed a new generation PACS (Picture Archiving and Communication System) based on artificial intelligent visualization. It is developed from our GRIDPACS (patent number: US8805890), which combined with IHE XDS-I profile, to implement images communication, storage and display. It also uses 3D anatomical visualization model to extract multi-source data from PACS/RIS/HIS/EMR, to express patient disease location, size and severity, which was introduced as Visual Patent (VP) at previous SPIE Medical Imaging (SPIE MI 2018). It can integrate the training model of AI Imaging Diagnosis, to mark the focus and display the disease trends. The system not only has the original PACS functions, but also realizes the man-machine interaction (images and electronic medical record information between radiologist and patient) in a personalized, fast, comprehensive, quantitative and easy-to-understand way. It can be used in various medical institutions, image diagnostic centers, and imaging cloud, to support the healthy development of imaging technology in China.
KEYWORDS: Medical imaging, Artificial intelligence, Clouds, Data communications, Internet, Picture Archiving and Communication System, Image processing, Mobile devices, Cancer, Document imaging
This paper proposed a new approach to design medical imaging-sharing service network based on professional medical imaging center (PMIC). PMIC is famous for advanced imaging modalities and expert resources. The network connects clinics, hospitals and PMICs to provide collaborative diagnosis, consultation, mobile expert consulting and medical imaging artificial intelligence (AI) analysis services through Internet. It allows patients to be registered in hospital and examined in PMIC. It provides to schedule and view patients exam from mobile devices. It also provides AI analysis for some specific kinds of medical images such as carotid plaque and mammary cancer, to help doctors get accurate conclusions. The network is flexible to use three layers architecture with secure messaging and data communication: data source, service cloud and service provider. It has been deployed in Guangzhou Huyun Medical Imaging Diagnosis Center since July 2018 to provide services for the First People’s Hospital of Guangzhou.
The benign and malignant differential diagnosis of small pulmonary nodules (diameter < 20 mm) found in lung CT images is big challenges for most of radiologists. Here, we presented our preliminary study of benign and malignant differentiation of small pulmonary nodules in lung CT images by using deep learning Convolutional Neural Network (CNN). The 921 cases with small benign and malignant pulmonary nodules confirmed by pathology were collected from three data sources and were used to train and validate the CNN. The preliminary results of AUCs of ROC curves for differentiating benign and malignant pulmonary small nodules with various types and sizes of solid, semi-solid and ground glass nodules were presented and discussed.
In this presentation, we presented a new approach to design cloud-based image sharing network for collaborative imaging diagnosis and consultation through Internet, which can enable radiologists, specialists and physicians locating in different sites collaboratively and interactively to do imaging diagnosis or consultation for difficult or emergency cases. The designed network combined a regional RIS, grid-based image distribution management, an integrated video conferencing system and multi-platform interactive image display devices together with secured messaging and data communication. There are three kinds of components in the network: edge server, grid-based imaging documents registry and repository, and multi-platform display devices. This network has been deployed in a public cloud platform of Alibaba through Internet since March 2017 and used for small lung nodule or early staging lung cancer diagnosis services between Radiology departments of Huadong hospital in Shanghai and the First Hospital of Jiaxing in Zhejiang Province.
Online peer to peer medical consultation between doctors such as physicians and specialists in China has a broad market demand and has been continuously accepted. For some difficult diseases, electronic medical records with medical images are required to present to both sides at same time during the consultation so that both sides can manipulate the records interactively to understand the medical meanings of the records, especially images. Here, we presented design of a teleconsultation system integrated with a cloud-based collaborative image sharing network to provide online peer-to-peer medical consultation for difficult cases with multi-media medical records including DICOM images. The presented teleconsultation system provides bidirectional interactive manipulations on images presented to peer-to-peer sides and has been used for small lung nodule diagnosis services between Huadong hospital in Shanghai and Jiaxing First Hospital in Zhejiang Province through Internet.
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