Combining Sparse and Dense Features to Improve Multi-Modal Registration for Brain DTI Images.

Simona Moldovanu, Lenuta Pană Toporaș, Anjan Biswas, Luminita Moraru

Abstract read

In one paragraph

Article in Entropy (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it

0cells of the map it votes in

3citing 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

3 citing papers in PubMed.

An NLP-based technique to extract meaningful features from drug SMILES.iScience · 2024
Article
Combining CNNs and Markov-like Models for Facial Landmark Detection with Spatial Consistency Estimates.Journal of imaging · 2023
Article
A Medical Image Registration Method Based on Progressive Images.Computational and mathematical methods in medicine · 2021
Article

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

4 authors.

Simona MoldovanuDepartment of Computer Science and Information Technology, Faculty of Automation, Computers, Electrical Engineering and Electronics, Dunarea de Jos University of Galati, Galati 47 Domneasca Str., 800008 Galati, Romania.ORCID 0000-0002-5934-329X

Lenuta Pană ToporașThe Modelling & Simulation Laboratory, Dunarea de Jos University of Galati, Galati 47 Domneasca Str., 800008 Galati, Romania.

Anjan BiswasDepartment of Physics, Chemistry and Mathematics, Alabama A&M University, Normal, AL 35762-4900, USA.

Luminita MoraruThe Modelling & Simulation Laboratory, Dunarea de Jos University of Galati, Galati 47 Domneasca Str., 800008 Galati, Romania.ORCID 0000-0002-9121-5714

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A new solution to overcome the constraints of multimodality medical intra-subject image registration is proposed, using the mutual information (MI) of image histogram-oriented gradients as a new matching criterion. We present a rigid, multi-modal image registration algorithm based on linear transformation and oriented gradients for the alignment of T2-weighted (T2w) images (as a fixed reference) and diffusion tensor imaging (DTI) (

Indexed as

fiducial registration errorhistogram-oriented gradientsimage registrationmutual informationsparse and dense features

Identifiers

PMID33287067

DOI10.3390/e22111299

PMCPMC7711905

What OpenQuestion holds

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LicenceCC BY

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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.