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BEST IN PHYSICS (THERAPY): Develop a Web-Based Brain Metastases Segmentation Platform with Atlas Label for Stereotactic Radiosurgery

H Liu1*, Y Liu2 , S Stojadinovic3 , Z Wardak4 , W Lu5 , Y Yan6 , S Jiang7 , R Timmerman8 , L Nedzi9 , T Dan10 , X Gu11 , (1) UT Southwestern Medical Center, Dallas, TX, (2) Sichuan University, Chengdu, ,(3) UT Southwestern Medical Center, Dallas, TX, (4) UT Southwestern Medical Center, Dallas, TX, (5) UT Southwestern Medical Center, Dallas, TX, (6) UT Southwestern Medical Center, Dallas, TX, (7) UT Southwestern Medical Center, Dallas, TX, (8) UT Southwestern Medical Center, Dallas, TX, (9) UT Southwestern Medical Center, Dallas, TX, (10) UT Southwestern Medical Center, Dallas,TX ,(11) UT Southwestern Medical Center, Dallas, TX

Presentations

(Thursday, 7/18/2019) 1:00 PM - 3:00 PM

Room: 304

Purpose: To develop an automated brain metastases (BMs) segmentation platform with atlas labelling for efficient stereotactic radiosurgery treatment planning and treatment follow-up.

Methods: A web-based BMs segmentation platform was implemented on Django web framework, including both client side and back-end server. On client side, JavaScript 3D medical image viewer was adopted for visualizing DICOM and NIFIT formats images. The back-end server runs multiple image processing and segmentation algorithms to accomplish BMs segmentation and labelling, including: 1) skull removing using a learning based ROBEX algorithm; 2) a deep-learning based BMs segmentation algorithm; 3) atlas registration-based BMs labelling. Automatically segmented BMs contours are sent back to web client for reviewing/modification. The finalized contour sets are saved in a DICOM RTStruct format.

Results: We evaluated our developed platform performance on patients having BMs varied from 1-60. The platform takes 4-5 minutes in average to finish segmentation and labelling. Compared to manual segmentation/labelling, this offers substantial clinical time savings and workflow improvement.

Conclusion: A web-based BMs segmentation was developed and evaluated. The developed tool can be a useful tool for assisting radiosurgery treatment planning and treatment follow-up.

Keywords

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