Using CT Images from the MICCAI 2015 — Head and Neck Auto Segmentation challenge

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Radiotherapy is now a common approach to treat cancers in the Head-and-Neck (HaN) region. To ensure that healthy organs are exposed to a minimal amount of tumor-killing radiation, it is required to segment them. Automated segmentation of such organs is required since there exists inter-annotator (i.e. between radiation oncologists) variations…

Leveraging the tf.function decorator to reduce time and memory requirements in custom tensorflow loops.

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This post is the second in a series on writing efficient training code in Tensorflow 2.x for 3D medical image segmentation. , we saw how one can extract sub-volumes from 3D CT volumes using the tf.data.Dataset API. Here, the focus is on writing custom training loops with a specific focus…

An understanding of open data sets for urban semantic segmentation shall help one understand how to proceed while training models for self-driving cars.

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Myriad efforts have been made over the last 10 years in algorithmic improvements and dataset creation for semantic segmentation tasks. Of late, there have been rapid gains in this field, a subset of visual scene understanding, due mainly to contributions by deep learning methodologies. But deep…

Prerak Mody

I'm a PhD Candidate at Leiden University Medical Centre. My research focuses on using deep learning for contour propagation of Organs at Risk in CT images.

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