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6 March 2018 The development of an ophthalmologic imaging CADe structured report for retinal image radiomics research
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Retinal changes on a fundus image have been found to be related to a series of diseases. The traditional retinal image quantitative features are usually collected by various standalone and proprietary software which results in variabilities in feature extraction and data collection. Based on our previously established web-based imaging informatics platform to view DICOMized and de-identified fundus images, we developed a computer aided detection structured report (CADe SR) to capture some of the quantitative features on fundus images such as arteriole/venule diameter ratio, cup/disc diameter ratio and to record several lesions such as aneurysms, hemorrhages, neovascularization and exudates into different regions based on known research and clinically related templates such as Early Treatment Diabetic Retinopathy Study (ETDRS) 9 Region Map and four Region Map. In this way, the location patterns of the above lesions as well as morphological changes of anatomy structures could be saved in SR for further radiomics research. In addition, an on-line consultation tool was developed to facilitate further discussion among clinicians and researchers regarding any uncertainty of measurements. Compared with the present workflow of utilizing standalone software to obtain quantitative results, qualitative and quantitative data was acquired by the CADe SR directly, which will provide researchers and clinicians the ability to capture findings and will foster future image-based knowledge discovery researches.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Huiqun Wu, Joseph Liu, Siliang Zhang, Alyssa Zhu, Christopher Sulistio, Jingjing Li, Aimin Sang, Jiancheng Dong, and Brent J. Liu "The development of an ophthalmologic imaging CADe structured report for retinal image radiomics research", Proc. SPIE 10579, Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications, 1057910 (6 March 2018);

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