mlchen666 / PituitaryMicroadenomaDiagnosis

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Pituitary Microadenoma Diagnosis using Deep Learning

This repository contains the source code of PM-CAD system which is described in our paper "Automatic diagnosis of pituitary microadenoma from magnetic resonance imaging using deep learning algorithms". The PM-CAD system is a computer-aided diagnosis system aiming to diagnose pituitary microadenoma from MRI using deep learning techniques.


  • pytorch >= 1.6.0
  • SimpleITK >= 1.1.0
  • albumentations >= 0.4.3
  • tensorflow >= 2.0.0
  • numpy >=1.16.3
  • opencv-Python >=
  • matplotlib >= 2.2.2
  • tqdm >= 4.46.0


Download the checkpoints from BaiduYunPan [Link] with code frnp.


We provide a snippet code to demonstrate how to diagnose pituitary microadenomas using our method, run by:

python --path=Dataset/Demo/pituitary_microadenoma_case


To train the pituitary detection model:

cd DetectionModel
sh experiment/fasterrcnn/

To train the microadenomas diagnosis model (i.e., PM-Net):

cd DiagnosisModel
sh experiment/panet/

To train other microadenomas diagnosis models:

cd DiagnosisModel
sh experiment/baseline/
sh experiment/baseline/
sh experiment/baseline/
sh experiment/baseline/
sh experiment/baseline/
sh experiment/cnn3d/
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