ArticleJournal of healthcare engineering2018
An Improved Fuzzy Connectedness Method for Automatic Three-Dimensional Liver Vessel Segmentation in CT Images.
Article in Journal of healthcare engineering, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Performance and clinical applicability of machine learning in liver computed tomography imaging: a systematic review.European radiology · 2023Pooled it
- Towards Fixing Vessel Segmentation Breakage: A Systematic Review.Journal of clinical medicine · 2026Review
- Vascular liver segmentation: a narrative review on methods and new insights brought by artificial intelligence.The Journal of international medical research · 2024Review
- Design of Path-Planning System for Interventional Thermal Ablation of Liver Tumors Based on CT Images.Sensors (Basel, Switzerland) · 2024Article
- Clinical applications of artificial intelligence in liver imaging.La Radiologia medica · 2023Review
- Liver segmentation in CT imaging with enhanced mask region-based convolutional neural networks.Annals of translational medicine · 2021Article
- Computational Methods for Liver Vessel Segmentation in Medical Imaging: A Review.Sensors (Basel, Switzerland) · 2021Review
- Automatic Liver Segmentation in CT Images with Enhanced GAN and Mask Region-Based CNN Architectures.BioMed research international · 2021Article
- A novel method to model hepatic vascular network using vessel segmentation, thinning, and completion.Medical & biological engineering & computing · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper, an improved fuzzy connectedness (FC) method was proposed for automatic three-dimensional (3D) liver vessel segmentation in computed tomography (CT) images. The vessel-enhanced image (i.e., vesselness image) was incorporated into the fuzzy affinity function of FC, rather than the intensity image used by traditional FC. An improved vesselness filter was proposed by incorporating adaptive sigmoid filtering and a background-suppressing item. The fuzzy scene of FC was automatically initialized by using the Otsu segmentation algorithm and one single seed generated adaptively, while traditional FC required multiple seeds. The improved FC method was evaluated on 40 cases of clinical CT volumetric images from the 3Dircadb (
Indexed as
Identifiers
What OpenQuestion holds
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.