Dr. Liehang Shi Profile

Dr. Liehang Shi

at Shanghai Institute of Technical Physics

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Publications (3)

Proceedings Article | 6 March 2018 Paper

Hadoop-based implementation of processing medical diagnostic records for visual patient system

Yuanyuan Yang, Liehang Shi, Zhe Xie, Jianguo Zhang

Proceedings Volume 10579, 105791F (2018) https://doi.org/10.1117/12.2292311

KEYWORDS: Data processing, Visualization, Lithium, Imaging systems, Medical imaging, Picture Archiving and Communication System, Image processing, Medical diagnostics, Diagnostics, Virtual point source

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Proceedings Article | 19 April 2017 Presentation

Principle and engineering implementation of 3D visual representation and indexing of medical diagnostic records (Conference Presentation)

Liehang Shi, Jianyong Sun, Yuanyuan Yang, Tonghui Ling, Mingqing Wang, Jianguo Zhang

Proceedings Volume 10138, 101380Y (2017) https://doi.org/10.1117/12.2254727

KEYWORDS: Electronic imaging, Diagnostics, Visualization, Virtual point source, 3D visualizations, Picture Archiving and Communication System, 3D displays, Medical diagnostics, Medicine, Radiology

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Purpose: Due to the generation of a large number of electronic imaging diagnostic records (IDR) year after year in a digital hospital, The IDR has become the main component of medical big data which brings huge values to healthcare services, professionals and administration. But a large volume of IDR presented in a hospital also brings new challenges to healthcare professionals and services as there may be too many IDRs for each patient so that it is difficult for a doctor to review all IDR of each patient in a limited appointed time slot. In this presentation, we presented an innovation method which uses an anatomical 3D structure object visually to represent and index historical medical status of each patient, which is called Visual Patient (VP) in this presentation, based on long term archived electronic IDR in a hospital, so that a doctor can quickly learn the historical medical status of the patient, quickly point and retrieve the IDR he or she interested in a limited appointed time slot. Method: The engineering implementation of VP was to build 3D Visual Representation and Index system called VP system (VPS) including components of natural language processing (NLP) for Chinese, Visual Index Creator (VIC), and 3D Visual Rendering Engine.There were three steps in this implementation: (1) an XML-based electronic anatomic structure of human body for each patient was created and used visually to index the all of abstract information of each IDR for each patient; (2)a number of specific designed IDR parsing processors were developed and used to extract various kinds of abstract information of IDRs retrieved from hospital information systems; (3) a 3D anatomic rendering object was introduced visually to represent and display the content of VIO for each patient. Results: The VPS was implemented in a simulated clinical environment including PACS/RIS to show VP instance to doctors. We setup two evaluation scenario in a hospital radiology department to evaluate whether radiologists accept the VPS and how the VP impact the radiologists’ efficiency and accuracy in reviewing historic medical records of the patients. We got a statistical results showing that more than 70% participated radiologist would like to use the VPS in their radiological imaging services. In comparison testing of using VPS and RIS/PACS in reviewing historic medical records of the patients, we got a statistical result showing that the efficiency of using VPS was higher than that of using PACS/RIS. New Technologies and Results to be presented: This presentation presented an innovation method to use an anatomical 3D structure object, called VP, visually to represent and index historical medical records such as IDR of each patient and a doctor can quickly learn the historical medical status of the patient through VPS. The evaluation results showed that VPS has better performance than RIS-integrated PACS in efficiency of reviewing historic medical records of the patients. Conclusions: In this presentation, we presented an innovation method called VP to use an anatomical 3D structure object visually to represent and index historical IDR of each patient and briefed an engineering implementation to build a VPS to implement the major features and functions of VP. We setup two evaluation scenarios in a hospital radiology department to evaluate VPS and achieved evaluation results showed that VPS has better performance than RIS-integrated PACS in efficiency of reviewing historic medical records of the patients.

Proceedings Article | 25 March 2016 Paper

Semantic information extracting system for classification of radiological reports in radiology information system (RIS)

Liehang Shi, Tonghui Ling, Jianguo Zhang

Proceedings Volume 9789, 97890T (2016) https://doi.org/10.1117/12.2216183

KEYWORDS: Radiology, Imaging informatics, Statistical analysis, Classification systems, Imaging systems, Data hiding, Data modeling, Physics, Rule based systems, Computing systems, Computed tomography, Lung, Pattern recognition, Statistical modeling, X-rays

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