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Abstract #3795

Automated analysis of eye tumor MR-images for an improved treatment determination

Mohamed Kilany Hassan1, Denis Shamonin1, Rahil Shahzad1, Andrew Webb1, Berend Stoel1, and Jan-Willem Beenakker1,2

1Radiology, LUMC, Leiden, Netherlands, 2Ophthalmology, LUMC, Leiden, Netherlands

The optimal treatment for uveal melanoma, the most common primary malignant eye tumor, depends on tumor thickness. Conventionally tumor thickness is determined with 2D ultrasound, but MRI allows for a full 3D analysis. It is, however, often difficult to determine the maximum tumor thickness due to its complex 3D shape. We propose a fully automatic framework to segment these MR-images to measure the tumor thickness accurately and evaluate it in four patients. The proposed method has a direct impact on the clinical practice, as a more accurate 3D assessment of the tumor dimensions directly influences therapy determination.

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