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

Photo by Craig Cameron on Unsplash
  • Data…


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

Photo by National Cancer Institute on Unsplash


Photo by National Cancer Institute on Unsplash


Efficient extraction of medical image subvolumes for a head and neck segmentation dataset

Photo by National Cancer Institute on Unsplash


Loss Curves showing improved segmentation over epochs (Photo by Playment)

Basic Definitions

L2 LOSS

  • This is the most basic loss available and is also called as the Euclidean loss. This relies on the…


MicroDicom Viewer with its three main panes

Layout

The viewer contains three main windows — DICOM Browser, Image Viewer and the DICOM Tags Pane (from left to right)

Advantages

  • Computationally light weight
  • Fast loading of DICOM data
  • DICOM Tag Browser — Compared to other viewers such as 3D Slicer, MeVisLab, MicroDicom has…


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

What is Semantic Segmentation?

The task of Semantic Segmentation is to annotate every pixel of an image with an object class. These classes could…

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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