OCT_DDA

This is the source code for Paper "Cross-domain retinopathy classification with optical coherence tomography images via a novel deep domain adaptation method"

Pre-request

1. Download the pretrained vgg16 model from https://download.pytorch.org/models/vgg16_bn-6c64b313.pth

Split the dataset by person

1. Run the python code CELL_data_split.py to split CELL dataset
2. Run the python code BOE_data_split_by_person.py to split BOE dataset
3. Run the python code TMI_data_split_by_person.py to split TMI dataset

Benchmark methods

1. Run the python code ADDA_vgg16_train.py for ADDA
2. Run the python code CAT_vgg16_train.py for CAT
3. Run the python code DDC_vgg16__train.py for DDC

Proposed DDA method

1. Run the python code ADDA_EM_vgg16_train.py for proposed method