ild-cnn
Lung Classifier
Develops a deep convolutional neural network to classify lung patterns in interstitial lung diseases
This is supplementary material for the manuscript: "Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network" M. Anthimopoulos, S. Christodoulidis, L. Ebner, A. Christe and S. Mougiakakou, IEEE Transactions on Medical Imaging (2016)
24 stars
2 watching
18 forks
Language: Python
last commit: over 8 years ago
Linked from 1 awesome list
Related projects:
Repository | Description | Stars |
---|---|---|
bmirds/deepslide | Classifies high-resolution microscopy images of lung adenocarcinoma using deep neural networks with a sliding window framework. | 489 |
imlab-uiip/lung-segmentation-2d | A deep learning model for segmenting lung tissue from 2D chest X-ray images using a UNet architecture. | 172 |
ahmedfgad/numpycnn | An implementation of a convolutional neural network (CNN) using NumPy for basic classification tasks. | 570 |
ibbm/cascaded-fcn | An implementation of a Cascaded Fully Convolutional Neural Network architecture for medical image segmentation | 304 |
lonl/cdbn | An implementation of a neural network architecture for image classification using convolutional and belief propagation techniques. | 35 |
matlab-deep-learning/abnormal-eeg-signal-classification-using-cnns | Develops and trains a deep neural network to classify EEG signals as normal or abnormal | 48 |
ethanhe42/u-net | A convolutional neural network architecture for biomedical image segmentation | 426 |
liuquande/feddg-elcfs | A framework for federated learning on medical image segmentation using continuous frequency space interpolation. | 240 |
cauchyturing/ucr_time_series_classification_deep_learning_baseline | Developing and evaluating deep learning models for time series classification with a focus on interpretability and deployability. | 677 |
cszn/ircnn | This project trains deep CNN denoisers to improve image restoration tasks such as deblurring and demosaicking through model-based optimization methods. | 600 |
ahmedfgad/cnngenetic | Trains convolutional neural networks using the genetic algorithm | 22 |
med-air/fedbn | An approach to federated learning that addresses feature shift non-iid by normalizing local batch features before averaging models. | 231 |
fyu/drn | An open-source implementation of dilated residual networks for image classification and segmentation tasks. | 1,105 |
ibm/max-inception-resnet-v2 | An image classification model using a third-generation deep residual network. | 28 |
homles11/igcv3 | An implementation of an efficient deep neural network architecture | 189 |