Dr. Haixing Li Profile

Dr. Haixing Li

at Shenyang Institute of Automation CAS

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 27 March 2022 Paper

LPM-GAN: lumbar paraspinal muscle segmentation using a generative adversarial network

Haixing Li, Haibo Luo, Huan Wang, Chongnan Yan, Lanbo Wang, Yueming Mu, Yunpeng Liu

Proceedings Volume 12169, 121694J (2022) https://doi.org/10.1117/12.2624128

KEYWORDS: Image segmentation, Spine, Magnetic resonance imaging, Medical imaging, Convolution, Visualization

Read Abstract +

After posterior lumbar surgeries (PLS), the change of the cross-sectional area(CSA) and fatty infiltration (FI) of paraspinal muscle can deeply affect the muscle activity pattern and spinal stability. The objective of this work is to perform automated paraspinal muscle (multifidus and erector spine) segmentation in magnetic resonance imaging (MRI) image. However, no work has achieved the semantic segmentation of multifidus (MF) and erector spinae (ES) due to three unusual challenges: (1) the distribution of paraspinal muscle overlaps with the distribution of other anatomical structures; (2) the fascia between MF and ES is unclear; (3) the intra- and inter-patient shape is variable. In this paper, we proposed a generative adversarial network called LPM-GAN which contains a generator and a discriminator to resolve above challenges. The generator solves the high variability and variety of paraspinal muscle through extracting high-level semantics of images and preserving the paraspinal muscle anatomy. And then, the discriminator is trained to optimize the predicted mask to make it closer to ground truth. Finally, we obtain the CSA and FI of paraspinal muscle by utilizing Otsu. Extensive experiments on MRIs of 69 patients have demonstrated that LPM-GAN achieves high Recall of 0.931 and 0.904, and Dice coefficient of 0.920 and 0.903, which reveals the method is effective.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years