Blog

Sep 8, 2017 - I joined the Swimming Club of UGA.


July 2017: Deep Learning

for Image Processing With Medical Applications

Project for Deep Learning and Medical Diagnosis


Diabetic retinopathy (DR) is the fastest growing cause of blindness, with nearly 415 million diabetic patients at risk worldwide. If caught early, the disease can be treated; if not, it can lead to irreversible blindness. Unfortunately, medical specialists capable of detecting the disease are not available in many parts of the world where diabetes is prevalent. Machine Learning can help doctors identify patients in need, particularly among underserved populations.


Figure 1. Examples of retinal fundus photographs that are taken to screen for DR. The image on the left is of a healthy retina (A), whereas the image on the right is a retina with referable diabetic retinopathy (B) due a number of hemorrhages (red spots) present.

So here I am sharping my tools (Open CV) and Python to see how can I dive into in this very interesting data set.



DATASETS are coming from the Kaggle Website which is provided by California Healthcare Foundation. and the data is very nicely devidide into training and testing along with severity of the detection

  • train.zip.* - the training set (5 files total)
  • test.zip.* - the test set (7 files total)
  • sample.zip - a small set of images to preview the full dataset
  • sampleSubmission.csv - a sample submission file in the correct format
  • trainLabels.csv - contains the scores for the training set