ArticleInternational journal of computer assisted radiology and surgery2016
Automatic segmentation and analysis of the main pulmonary artery on standard post-contrast CT studies using iterative erosion and dilation.
Article in International journal of computer assisted radiology and surgery, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Automated Segmentation of Tissues Using CT and MRI: A Systematic Review.Academic radiology · 2019Pooled it
- A new segment method for pulmonary artery and vein.Health information science and systems · 2023Article
- Automated 3D Segmentation of the Aorta and Pulmonary Artery on Non-Contrast-Enhanced Chest Computed Tomography Images in Lung Cancer Patients.Diagnostics (Basel, Switzerland) · 2022Article
- Automated Deep Learning Analysis for Quality Improvement of CT Pulmonary Angiography.Radiology. Artificial intelligence · 2022Article
- 3D Pulmonary Artery Segmentation from CTA Scans Using Deep Learning with Realistic Data Augmentation.Image analysis for moving organ, breast, and thoracic images : third International Workshop, RAMBO 2018, fourth International Workshop, BIA 2018, and first International Workshop, TIA 2018, held in conjunction with MICCAI 2018, Granada,... · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo describe an algorithm for the accurate segmentation of the main pulmonary artery (MPA) and determining its length, mid-cross-sectional area and mid-circumferential perimeter. This will help with accurate, rapid and reproducible MPA measurements which can be used to detect diseases that cause raised pulmonary arterial pressure, and allow standardized serial measurements to assess progression or response to treatment.
methodWe perform MPA segmentation using a novel approach based on erosion and dilation. A centerline is then determined by skeletonization, graph construction and spline fitting. MPA cross sections perpendicular to the centerline are analyzed in order to determine MPA length, and mid-cross-sectional area and perimeter. The technique was developed using four normal chest CT data sets and then tested on twenty normal post-contrast chest CT studies. Results are compared to manual segmentation and measurement by a thoracic radiologist.
resultsThe mean MPA length, mid-cross-sectional area and mid-circumferential perimeter of the twenty test data sets, calculated by our algorithm, are 43.6 [Formula: see text] 9.2 mm, 552.9 [Formula: see text] 132.4[Formula: see text] and [Formula: see text], respectively, compared with [Formula: see text] and [Formula: see text] obtained manually by the radiologist. Our technique shows high correlation with the manually determined parameters for both mid- cross-sectional area ([Formula: see text]) and length ([Formula: see text]), and good correlation for mid-circumferential perimeter ([Formula: see text]).
conclusionOur algorithm is a robust accurate automated method for obtaining measurements of the MPA. This allows a more standardized method for determining length, and mid- cross-sectional area/perimeter and therefore allows more accurate comparison of MPA measurements.
Indexed as
Identifiers
26410842What 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.