DeepAI
Log In Sign Up

Deep multiscale convolutional feature learning for weakly supervised localization of chest pathologies in X-ray images

08/22/2018
by   Suman Sedai, et al.
0

Localization of chest pathologies in chest X-ray images is a challenging task because of their varying sizes and appearances. We propose a novel weakly supervised method to localize chest pathologies using class aware deep multiscale feature learning. Our method leverages intermediate feature maps from CNN layers at different stages of a deep network during the training of a classification model using image level annotations of pathologies. During the training phase, a set of layer relevance weights are learned for each pathology class and the CNN is optimized to perform pathology classification by convex combination of feature maps from both shallow and deep layers using the learned weights. During the test phase, to localize the predicted pathology, the multiscale attention map is obtained by convex combination of class activation maps from each stage using the layer relevance weights learned during the training phase. We have validated our method using 112000 X-ray images and compared with the state-of-the-art localization methods. We experimentally demonstrate that the proposed weakly supervised method can improve the localization performance of small pathologies such as nodule and mass while giving comparable performance for bigger pathologies e.g., Cardiomegaly

READ FULL TEXT

page 1

page 2

page 3

page 4

01/25/2021

Weakly Supervised Thoracic Disease Localization via Disease Masks

To enable a deep learning-based system to be used in the medical domain ...
05/09/2019

Learning Interpretable Features via Adversarially Robust Optimization

Neural networks are proven to be remarkably successful for classificatio...
03/28/2019

InfoMask: Masked Variational Latent Representation to Localize Chest Disease

The scarcity of richly annotated medical images is limiting supervised d...
10/31/2020

Weakly Supervised 3D Classification of Chest CT using Aggregated Multi-Resolution Deep Segmentation Features

Weakly supervised disease classification of CT imaging suffers from poor...
09/23/2019

HR-CAM: Precise Localization of Pathology Using Multi-level Learning in CNNs

We propose a CNN based technique that aggregates feature maps from its m...
01/06/2019

Automated Multiscale 3D Feature Learning for Vessels Segmentation in Thorax CT Images

We address the vessel segmentation problem by building upon the multisca...