Search Results for author:
Found 4 papers, 3 papers with code
Evaluation of automated airway morphological quantification for assessing fibrosing lung disease
AirQuant is an open-source pipeline that avoids limitations of existing airway quantification algorithms and has clinical interpretability.
Interactive Medical Image Segmentation using Deep Learning with Image-specific Fine-tuning
Experimental results show that 1) our model is more robust to segment previously unseen objects than state-of-the-art CNNs; 2) image-specific fine-tuning with the proposed weighted loss function significantly improves segmentation accuracy; and 3) our method leads to accurate results with fewer user interactions and less user time than traditional interactive segmentation methods.
NiftyNet: a deep-learning platform for medical imaging
NiftyNet provides a modular deep-learning pipeline for a range of medical imaging applications including segmentation, regression, image generation and representation learning applications.
DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation
We propose a deep learning-based interactive segmentation method to improve the results obtained by an automatic CNN and to reduce user interactions during refinement for higher accuracy.
