Mr. Wei Zheng Profile

Wei Zheng

at Dartmouth College

SPIE Involvement:

Author

Publications (2)

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 | 13 March 2006 Paper

Measuring blood delivery to solitary pulmonary nodules using perfusion magnetic resonance imaging

Wei Zheng, Zhifeng Wang, Li Shen, Ling Gao, James Ford, Fillia Makedon, Justin Pearlman

Proceedings Volume 6143, 614332 (2006) https://doi.org/10.1117/12.652866

KEYWORDS: Magnetic resonance imaging, Tissues, Blood, Tumors, Blood vessels, Image segmentation, Lung cancer, Image registration, Medical imaging, Lithium

Read Abstract +

With perfusion magnetic resonance imaging (pMRI), perfusion describes the amount of blood passing through a block of tissue in a certain period of time. In pMRI, the tissue having more blood passing through will show higher intensity value as more contrast-labeled blood arrives. Perfusion reflects the delivery of essential nutrients to a block of tissue, and is an important parameter for the tissue status. Considering solitary pulmonary nodules (SPN), perfusion differences between malignant and benign nodules have been studied by different techniques. Much effort has been put into its characterization. In this paper, we proposed and implemented extraction of the SPN time intensity profile to measure blood delivery to solitary pulmonary nodules, describing their perfusion effects. In this method, a SPN time intensity profile is created based on intensity values of the solitary pulmonary nodule in lung pMRI images over time. This method has two steps: nodule tracking and profile clustering. Nodule tracking aligns the solitary pulmonary nodule in pMRI images taken at different time points, dealing with nodule movement resulted from breathing and body movement. Profile clustering implements segmentation of the nodule region and extraction of the time intensity profile of a solitary pulmonary nodule. SPN time intensity profiles reflect patterns of blood delivery to solitary pulmonary nodules, giving us a description of perfusion effect and indirect evidence of tumor angiogenesis. Analysis on SPN time intensity profiles will help the diagnosis of malignant nodules for early lung cancer detection.

Proceedings Article | 10 March 2006 Paper

Spatio-temporal analysis tool for modeling pulmonary nodules in MR images

Li Shen, Heng Huang, James Ford, Chia-Hsin Lu, Ling Gao, Wei Zheng, Fillia Makedon, Justin Pearlman

Proceedings Volume 6141, 61412I (2006) https://doi.org/10.1117/12.654469

KEYWORDS: Image segmentation, Image registration, Magnetic resonance imaging, Lung cancer, Lung, Cancer, Image processing, Visualization, Tumors, Principal component analysis

Read Abstract +

To detect lung cancer at an earlier stage, a promising method is to apply perfusion magnetic resonance imaging (pMRI) modified to assess tumor angiogenesis. One key issue is to effectively characterize angiogenic patterns of pulmonary nodules. Based on our previous study addressing this issue, in this work, we develop STAT, a Spatio-Temporal Analysis Tool that implements not only our previously proposed pulmonary nodule modeling framework but also a user friendly interface and many extended functions. Our goal is to make STAT an easy-to-use tool that can be applied to more general cases. STAT employs the following overall strategy for modeling pulmonary nodules: (1) nodule identification using a correlation maximization method, (2) nodule segmentation using edge detection, morphological operations and model-based strategy, and (3) nodule registration using landmark approach and thin-plate spline interpolation. In nodule identification, STAT provides new schemes for selecting the template and refining results in difficult cases. In nodule segmentation, STAT provides additional flexibilities for creating the weighting mask, selecting morphological structure elements and individually fixing segmentation result. In nodule registration, our previous study uses principal component analysis for landmark extraction, which may not work in general. To overcome this limitation, STAT provides an enhanced approach that minimizes the bending energy of the thin plate spline interpolation or mean square distance between each landmark set and the template set. Our main application of STAT is to define blood arrival patterns in the lung to identify tumor angiogenesis as a means of early accurate diagnosis of cancer.

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