Evidence map›Paper›PMID 38685979›Full record

ArticleShape in medical imaging : International Workshop, ShapeMI 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings. ShapeMI (Workshop) (2023 : Vancouver, B.C.)2023

Particle-Based Shape Modeling for Arbitrary Regions-of-Interest.

Hong Xu, Alan Morris, Shireen Y Elhabian

Abstract read
In one paragraph

Article in Shape in medical imaging : International Workshop, ShapeMI 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings. ShapeMI (Workshop) (2023 : Vancouver, B.C.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Hong XuScientific Computing and Imaging Institute, School of Computing, University of Utah, Salt Lake City, UT, USA.
Alan MorrisScientific Computing and Imaging Institute, School of Computing, University of Utah, Salt Lake City, UT, USA.
Shireen Y ElhabianScientific Computing and Imaging Institute, School of Computing, University of Utah, Salt Lake City, UT, USA.

Funding

ShapeWorks in the CloudR01AR076120 · NIAMS · UNIVERSITY OF UTAH · PI ELHABIAN, SHIREEN YOUSSEF · 2019 to 2024
$2.7M
ShapeWorksStudio: An Integrative, User-Friendly, and Scalable Suite for Shape Representation and AnalysisU24EB029011 · NIBIB · UNIVERSITY OF UTAH · PI ELHABIAN, SHIREEN YOUSSEF · 2019 to 2023
$1.4M
NIAMS NIH HHS R01 AR076120NIBIB NIH HHS U24 EB029011
6 · The paper itself

Abstract

Statistical Shape Modeling (SSM) is a quantitative method for analyzing morphological variations in anatomical structures. These analyses often necessitate building models on targeted anatomical regions of interest to focus on specific morphological features. We propose an extension to particle-based shape modeling (PSM), a widely used SSM framework, to allow shape modeling to arbitrary regions of interest. Existing methods to define regions of interest are computationally expensive and have topological limitations. To address these shortcomings, we use mesh fields to define free-form constraints, which allow for delimiting arbitrary regions of interest on shape surfaces. Furthermore, we add a quadratic penalty method to the model optimization to enable computationally efficient enforcement of any combination of cutting-plane and free-form constraints. We demonstrate the effectiveness of this method on a challenging synthetic dataset and two medical datasets.

Identifiers

PMID38685979
PMCPMC11057367

What OpenQuestion holds

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Registered trials

None linked

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.