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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