ArticleScientific reports2024
An effective and open source interactive 3D medical image segmentation solution.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Inter-Observer Reproducibility of [18F]FDG PET/CT Radiomic Features in Primary Breast Carcinoma.Journal of imaging · 2026Article
- Evaluating Safety and Anatomical Eligibility for Paranasal Implants in the Atrophic Maxilla: A Segmentation-Assisted Proof-of-Concept Study.Journal of clinical medicine · 2026Article
- Comparing Interactive Machine Learning and Unassisted Segmentation of Geographic Atrophy From Fundus Autofluorescence.Translational vision science & technology · 2026Article
- Quantification of visceral adipose tissue volume predicts both short-term and long-term transmural healing in patients with Crohn's disease receiving Ustekinumab.Therapeutic advances in gastroenterology · 2026Article
- Predicting Stereotactic Body Radiation Therapy Response Using an AI-Based Tumor Vessel Biomarker.Technology in cancer research & treatmentArticle
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Authors and funding
9 authors.
Funding
Abstract
3D medical image segmentation is a key step in numerous clinical applications. Even though many automatic segmentation solutions have been proposed, it is arguably that medical image segmentation is more of a preference than a reference as inter- and intra-variability are widely observed in final segmentation output. Therefore, designing a user oriented and open-source solution for interactive annotation is of great value for the community. In this paper, we present an effective interactive segmentation method that employs an adaptive dynamic programming approach to incorporates users' interactions efficiently. The method first initializes an segmentation through a feature-based geodesic computation. Then, the segmentation is further refined by using an efficient updating scheme requiring only local computations when new user inputs are available, making it applicable to high resolution images and very complex structures. The proposed method is implemented as a user-oriented software module in 3D Slicer. Our approach demonstrates several strengths and contributions. First, we proposed an efficient and effective 3D interactive algorithm with the adaptive dynamic programming method. Second, this is not just a presented algorithm, but also a software with well-designed GUI for users. Third, its open-source nature allows users to make customized modifications according to their specific requirements.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.