thinkfurther / RED_CNN

Pytorch Implementation of Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network (RED-CNN)

RED_CNN

Implementation of Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network (RED-CNN)

There is several things different from the original paper.

• The input image patch(55x55 size) is extracted randomly from the 512x512 size image. --> Original : Extract patches at regular intervals from the entire image.
• Masking the Hounsfield unit corresponding to the air and calculating the MSE loss. (The original MSE loss also proceeds)
• 512x512 entire image input is used without extracting the patches.

DATASET

• “the 2016 NIH-AAPM-Mayo Clinic Low Dose CT Grand Challenge” by Mayo Clinic
  https://www.aapm.org/GrandChallenge/LowDoseCT/

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RESULT