Accurate 2D soft segmentation of medical image via SoftGAN network

07/29/2020
by   Changwei Wang, et al.
0

Accurate 2D lung nodules segmentation from medical Computed Tomography (CT) images is crucial in medical applications. Most current approaches cannot achieve precise segmentation results that preserving both rich edge details description and smooth transition representations between image regions due to the tininess, complexities, and irregularities of lung nodule shapes. To address this issue, we propose a novel Cascaded Generative Adversarial Network (CasGAN) to cope with CT images super-resolution and segmentation tasks, in which the semantic soft segmentation form on precise lesion representation is introduced for the first time according to our knowledge, and lesion edges can be retained accurately after our segmentation that can promote rapid acquisition of high-quality large-scale annotation data based on RECIST weak supervision information. Extensive experiments validate that our CasGAN outperforms the state-of-the-art methods greatly in segmentation quality, which is also robust on the application of medical images beyond lung nodules. Besides, we provide a challenging lung nodules soft segmentation dataset of medical CT images for further studies.

READ FULL TEXT

page 2

page 3

page 4

page 5

page 6

page 7

page 9

research
09/16/2022

3D Matting: A Soft Segmentation Method Applied in Computed Tomography

Three-dimensional (3D) images, such as CT, MRI, and PET, are common in m...
research
09/14/2023

M3Dsynth: A dataset of medical 3D images with AI-generated local manipulations

The ability to detect manipulated visual content is becoming increasingl...
research
07/18/2018

CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement

Automated lesion segmentation from computed tomography (CT) is an import...
research
06/11/2018

CT-Realistic Lung Nodule Simulation from 3D Conditional Generative Adversarial Networks for Robust Lung Segmentation

Data availability plays a critical role for the performance of deep lear...
research
10/11/2022

3D Matting: A Benchmark Study on Soft Segmentation Method for Pulmonary Nodules Applied in Computed Tomography

Usually, lesions are not isolated but are associated with the surroundin...
research
04/16/2022

Multi-organ Segmentation Network with Adversarial Performance Validator

CT organ segmentation on computed tomography (CT) images becomes a signi...
research
07/11/2014

CIDI-Lung-Seg: A Single-Click Annotation Tool for Automatic Delineation of Lungs from CT Scans

Accurate and fast extraction of lung volumes from computed tomography (C...

Please sign up or login with your details

Forgot password? Click here to reset