A Comprehensive Web Annotation Application for Organ Image Segmentation and Predictive Inference
Pages 850 - 855
Abstract
In this paper, we present a web annotation application tailored to streamline the process of annotating 3D organ volumes using preprocessed 2D images data. Our platform introduces advanced annotation assistance and predictive inference to significantly enhance medical imaging workflows. Although we leverage curated sets of 2D images rather than the original 3D volume data, our innovative approach focuses on optimizing the annotation process and integrating predictive algorithms to improve accuracy. By capitalizing on the preprocessing step of 3D volume segmentation dataset, we offer a solution that expedites the creation of accurate organ segmentation, ultimately contributes to more efficient medical image analysis.
References
[1]
Yuri Boykov and Marie-pierre Jolly. 2001. Interactive Graph Cuts for Optimal Boundary & Region Segmentation of Objects in N-D Images. Proceedings. Eighth IEEE International Conference on Computer Vision: 2001. Vol.1 1 (07 2001), 105–112. https://doi.org/10.1109/ICCV.2001.937505
[2]
Chimezie Innocent. 2023. Google Sign In Guide. https://blog.logrocket.com/guide-adding-google-login-react-app/ Accessed: 2023-03-20.
[3]
Won-Dong Jang and Chang-Su Kim. 2019. Interactive Image Segmentation via Backpropagating Refinement Scheme. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2019), 5292–5301.
[4]
Kevis-Kokitsi Maninis, Sergi Caelles, Jordi Pont-Tuset, and Luc Van Gool. 2018. Deep Extreme Cut: From Extreme Points to Object Segmentation. arxiv:1711.09081 [cs.CV]
[5]
Eric Mortensen. 1998. Interactive Segmentation with Intelligent Scissors. Graphical Models and Image Processing 60 (09 1998), 349–384. https://doi.org/10.1006/gmip.1998.0480
[6]
Hiba Ramadan, Chaymae Lachqar, and H. Tairi. 2020. A survey of recent interactive image segmentation methods. Computational Visual Media (08 2020). https://doi.org/10.1007/s41095-020-0177-5
[7]
Carsten Rother, Vladimir Kolmogorov, and Andrew Blake. 2004. "GrabCut": Interactive Foreground Extraction Using Iterated Graph Cuts. ACM Trans. Graph. 23, 3 (aug 2004), 309–314. https://doi.org/10.1145/1015706.1015720
[8]
Konstantin Sofiiuk, Ilia Petrov, Olga Barinova, and Anton Konushin. 2020. f-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation. arxiv:2001.10331 [cs.CV]
[9]
Ning Xu, Brian Price, Scott Cohen, Jimei Yang, and Thomas Huang. 2016. Deep Interactive Object Selection. arxiv:1603.04042 [cs.CV]
[10]
Hongkai Yu, Youjie Zhou, Hui Qian, Min Xian, Yuewei Lin, Dazhou Guo, Kang Zheng, Kareem Abdelfatah, and Song Wang. 2015. LooseCut: Interactive Image Segmentation with Loosely Bounded Boxes. arxiv:1507.03060 [cs.CV]
Index Terms
- A Comprehensive Web Annotation Application for Organ Image Segmentation and Predictive Inference
Recommendations
Multiple Abdominal Organ Segmentation: An Atlas-Based Fuzzy Connectedness Approach
Organ segmentation is an important step in various medical image applications. In this paper, a presegmented atlas is incorporated into the fuzzy connectedness (FC) framework for automatic segmentation of abdominal organs. First, the atlas is registered ...
Random Walk and Graph Cut for Co-Segmentation of Lung Tumor on PET-CT Images
Accurate lung tumor delineation plays an important role in radiotherapy treatment planning. Since the lung tumor has poor boundary in positron emission tomography (PET) images and low contrast in computed tomography (CT) images, segmentation of tumor in ...
Synergistic arc-weight estimation for interactive image segmentation using graphs
We introduce a framework for synergistic arc-weight estimation, where the user draws markers inside each object (including background), arc weights are estimated from image attributes and object information (pixels under the markers), and a visual ...
Comments
Information & Contributors
Information
Published In
December 2023
1058 pages
ISBN:9798400708916
DOI:10.1145/3628797
Copyright © 2023 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 07 December 2023
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Funding Sources
- University of Science, VNU-HCM
Conference
SOICT 2023
SOICT 2023: The 12th International Symposium on Information and Communication Technology
December 7 - 8, 2023
Ho Chi Minh, Vietnam
Acceptance Rates
Overall Acceptance Rate 147 of 318 submissions, 46%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 31Total Downloads
- Downloads (Last 12 months)15
- Downloads (Last 6 weeks)0
Reflects downloads up to 01 Mar 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format