Mr. Jose Dolz Profile

Jose Dolz

Marie Curie Early Stage Researcher at AQUILAB

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 | 21 March 2014 Paper

Combining watershed and graph cuts methods to segment organs at risk in radiotherapy

Jose Dolz, Hortense Kirisli, Romain Viard, Laurent Massoptier

Proceedings Volume 9034, 90343Z (2014) https://doi.org/10.1117/12.2042768

KEYWORDS: Image segmentation, Radiotherapy, Computed tomography, Heart, Medical imaging, Liver, Image processing algorithms and systems, Spleen, Radiation oncology, Binary data

Read Abstract +

Computer-aided segmentation of anatomical structures in medical images is a valuable tool for efficient radiation therapy planning (RTP). As delineation errors highly affect the radiation oncology treatment, it is crucial to delineate geometric structures accurately. In this paper, a semi-automatic segmentation approach for computed tomography (CT) images, based on watershed and graph-cuts methods, is presented. The watershed pre-segmentation groups small areas of similar intensities in homogeneous labels, which are subsequently used as input for the graph-cuts algorithm. This methodology does not require of prior knowledge of the structure to be segmented; even so, it performs well with complex shapes and low intensity. The presented method also allows the user to add foreground and background strokes in any of the three standard orthogonal views – axial, sagittal or coronal - making the interaction with the algorithm easy and fast. Hence, the segmentation information is propagated within the whole volume, providing a spatially coherent result. The proposed algorithm has been evaluated using 9 CT volumes, by comparing its segmentation performance over several organs - lungs, liver, spleen, heart and aorta - to those of manual delineation from experts. A Dice´s coefficient higher than 0.89 was achieved in every case. That demonstrates that the proposed approach works well for all the anatomical structures analyzed. Due to the quality of the results, the introduction of the proposed approach in the RTP process will be a helpful tool for organs at risk (OARs) segmentation.

Proceedings Article | 21 March 2014 Paper

Interactive approach to segment organs at risk in radiotherapy treatment planning

Jose Dolz, Hortense Kirisli, Romain Viard, Laurent Massoptier

Proceedings Volume 9034, 90343S (2014) https://doi.org/10.1117/12.2042766

KEYWORDS: Image segmentation, Radiotherapy, Liver, Computed tomography, Kidney, Spleen, Heart, Image processing algorithms and systems, Lung, Medical imaging

Read Abstract +

Accurate delineation of organs at risk (OAR) is required for radiation treatment planning (RTP). However, it is a very time consuming and tedious task. The use in clinic of image guided radiation therapy (IGRT) becomes more and more popular, thus increasing the need of (semi-)automatic methods for delineation of the OAR. In this work, an interactive segmentation approach to delineate OAR is proposed and validated. The method is based on the combination of watershed transformation, which groups small areas of similar intensities in homogeneous labels, and graph cuts approach, which uses these labels to create the graph. Segmentation information can be added in any view – axial, sagittal or coronal -, making the interaction with the algorithm easy and fast. Subsequently, this information is propagated within the whole volume, providing a spatially coherent result. Manual delineations made by experts of 6 OAR - lungs, kidneys, liver, spleen, heart and aorta – over a set of 9 computed tomography (CT) scans were used as reference standard to validate the proposed approach. With a maximum of 4 interactions, a Dice similarity coefficient (DSC) higher than 0.87 was obtained, which demonstrates that, with the proposed segmentation approach, only few interactions are required to achieve similar results as the ones obtained manually. The integration of this method in the RTP process may save a considerable amount of time, and reduce the annotation complexity.

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