Tubular Shape Aware Data Generation for Semantic Segmentation in Medical Imaging

10/02/2020
by   Ilyas Sirazitdinov, et al.
6

Chest X-ray is one of the most widespread examinations of the human body. In interventional radiology, its use is frequently associated with the need to visualize various tube-like objects, such as puncture needles, guiding sheaths, wires, and catheters. Detection and precise localization of these tube-like objects in the X-ray images is, therefore, of utmost value, catalyzing the development of accurate target-specific segmentation algorithms. Similar to the other medical imaging tasks, the manual pixel-wise annotation of the tubes is a resource-consuming process. In this work, we aim to alleviate the lack of the annotated images by using artificial data. Specifically, we present an approach for synthetic data generation of the tube-shaped objects, with a generative adversarial network being regularized with a prior-shape constraint. Our method eliminates the need for paired image–mask data and requires only a weakly-labeled dataset (10–20 images) to reach the accuracy of the fully-supervised models. We report the applicability of the approach for the task of segmenting tubes and catheters in the X-ray images, whereas the results should also hold for the other imaging modalities.

READ FULL TEXT

page 3

page 4

page 5

page 6

page 8

research
07/12/2022

VertXNet: Automatic Segmentation and Identification of Lumbar and Cervical Vertebrae from Spinal X-ray Images

Manual annotation of vertebrae on spinal X-ray imaging is costly and tim...
research
12/28/2014

Metacarpal Bones Localization in X-ray Imagery Using Particle Filter Segmentation

Statistical methods such as sequential Monte Carlo Methods were proposed...
research
10/22/2020

High resolution weakly supervised localization architectures for medical images

In medical imaging, Class-Activation Map (CAM) serves as the main explai...
research
08/25/2021

Anomaly Detection in Medical Imaging – A Mini Review

The increasing digitization of medical imaging enables machine learning ...
research
08/20/2019

Endotracheal Tube Detection and Segmentation in Chest Radiographs using Synthetic Data

Chest radiographs are frequently used to verify the correct intubation o...
research
09/09/2019

Adversarial Policy Gradient for Deep Learning Image Augmentation

The use of semantic segmentation for masking and cropping input images h...
research
06/24/2023

Utilizing Segment Anything Model For Assessing Localization of GRAD-CAM in Medical Imaging

The introduction of saliency map algorithms as an approach for assessing...

Please sign up or login with your details

Forgot password? Click here to reset