Evidence map›Paper›PMID 22272215›Full record

ReviewComputational and mathematical methods in medicine2012

Recent advances in morphological cell image analysis.

Shengyong Chen, Mingzhu Zhao, Guang Wu, Chunyan Yao, Jianwei Zhang

Abstract readReview
In one paragraph

Review in Computational and mathematical methods in medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing 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

37 citing papers in PubMed.

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  11. Profiling DNA damage in 3D Histology Samples.Medical optical imaging and virtual microscopy image analysis : first International Workshop, MOVI 2022, held in conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings. MOVI (Workshop) (1st : 2022 : Singapore) · 2022
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  12. Review
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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

5 authors.

Shengyong ChenCollege of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China. sy@ieee.org
Mingzhu Zhao
Guang Wu
Chunyan Yao
Jianwei Zhang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper summarizes the recent advances in image processing methods for morphological cell analysis. The topic of morphological analysis has received much attention with the increasing demands in both bioinformatics and biomedical applications. Among many factors that affect the diagnosis of a disease, morphological cell analysis and statistics have made great contributions to results and effects for a doctor. Morphological cell analysis finds the cellar shape, cellar regularity, classification, statistics, diagnosis, and so forth. In the last 20 years, about 1000 publications have reported the use of morphological cell analysis in biomedical research. Relevant solutions encompass a rather wide application area, such as cell clumps segmentation, morphological characteristics extraction, 3D reconstruction, abnormal cells identification, and statistical analysis. These reports are summarized in this paper to enable easy referral to suitable methods for practical solutions. Representative contributions and future research trends are also addressed.

Indexed as

AlgorithmsCellsImage Processing, Computer-Assisted

Identifiers

PMID22272215
PMCPMC3261466

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.