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Abstract #2521

Automated contouring and ADC measurement of esophageal cancer with a fully convolutional network

Benjamin Charles Musall1, Steven Hsesheng Lin2, Penny Fang2, Brett Carter3, Amy Catherine Moreno2, Jong Bum Son1, Jeremiah Wayne Sanders1, and Jingfei Ma1

1Imaging Physics, MD Anderson Cancer Center, Houston, TX, United States, 2Radiation Oncology, MD Anderson Cancer Center, Houston, TX, United States, 3Diagnostic Radiology, MD Anderson Cancer Center, Houston, TX, United States

A Fully Convolutional Network (FCN) was developed and applied to the task of contouring esophageal tumors on diffusion weighted images. After proper training, tumor classification by the FCN demonstrated excellent agreement with tumor contours from an inter-reader agreement study in the validation images. The FCN was able to achieve correct tumor classification in most cases with respect to different tumor position and shapes, and in the presence of intratumoral esophageal lumen.

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