Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images

Last update: Sep 21, 2022

Related tags

Deep Learning deep-learning keras segmentation convolutional-neural-networks unet lung-segmentation

Overview

Lung Segmentation (2D)

Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images.

Demo

See the application of the model in Demo folder.

Implementation

Implemented in Keras(2.0.4) with TensorFlow(1.1.0) as backend.

Use of data augmentation for training required slight changes to keras ImageDataGenerator. Generator in image_gen.py applies same transformation to both the image and the label mask.

To use this implementation one needs to load and preprocess data (see load_data.py), train new model if needed (train_model.py) and use the model for generating lung masks (inference.py).

trained_model.hdf5 contains model trained on both data sets mentioned below.

Segmentation

Scores achieved on Montgomery and JSRT(With these masks. See preprocess_JSRT.py.) (Measured using 5-fold cross-validation):

	JSRT	Montgomery
IoU	0.971	0.956
Dice	0.985	0.972

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Comments

what is in th 'idx.cvs' and 'left lung'?

I don't Know what kind of data for this code. csv_path = '/path/to/JSRT/idx.csv' what kind of data in idx.cvs? Does 'filenames' include suffix? and what's in 'left lung' ? left = io.imread('/path/to/JSRT/Masks/left lung/' + filename[:-4] + '.gif') right = io.imread('/path/to/JSRT/Masks/right lung/' + filename[:-4] + '.gif')

opened by sybilWsybil 5
`preprocess_JSRT.py` cannot `reshape`

I'm guessing output of preprocess_JSRT.py must be used as input images for train_model.py. Is this correct? If yes, then on line 8, reshaping the ndarray to (2048, 2048) gives ValueError: cannot reshape array of size ${size_of_ndarray} into shape (2048,2048) on all original images from JSRT. Furthermore, I don't really follow why img = 1.0 - np.fromfile(path + filename, dtype='>u2') * 1. / 4096 (changing the values like that, regardless of the reshaping) is happening as preprocessing. Could you please give a quick explanation?

opened by sarahESL 4
Implementing the model on Montgomery Dataset

Thank you for sharing the code for lung segmentation here. I am trying to implement the code for Montgomery Dataset. Do I simply change JSRT with Montgomery in order to do that? Also, there is no csv file for this dataset, do I have to create it manually?

opened by shashankshekhardehradun 4
Value error while running model.fit

Did you run into any such errors?

ValueError: A target array with shape (8, 512, 512, 3) was passed for an output of shape (None, 512, 512, 1) while using as loss binary_crossentropy. This loss expects targets to have the same shape as the output.

opened by as4401s 0

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