Evidence map›Paper›PMID 26601004›Full record

ArticleBiomedical optics express2015

Automatic neuron segmentation and neural network analysis method for phase contrast microscopy images.

Jincheng Pang, Nurdan Özkucur, Michael Ren, David L Kaplan, Michael Levin, Eric L Miller

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomedical optics express, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.5field-weighted citation impact, top 9% of its field
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

2 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. 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

6 authors at 1 institution in 1 country.

Jincheng PangDeptment of Electrical and Computer Engineering, Tufts University, Medford, MA, 02155, USA.
Nurdan ÖzkucurDepartment of Biomedical Engineering, Tufts University, Medford, MA, 02155, USA ; Department of Biology, Tufts University, Medford, MA, 02155, USA.
Michael RenDepartment of Biomedical Engineering, Tufts University, Medford, MA, 02155, USA.
David L KaplanDepartment of Biomedical Engineering, Tufts University, Medford, MA, 02155, USA.
Michael LevinDepartment of Biology, Tufts University, Medford, MA, 02155, USA.
Eric L MillerDeptment of Electrical and Computer Engineering, Tufts University, Medford, MA, 02155, USA.
Tufts University · US

Funding

Electrotherapeutic strategies for connective tissue repairR01AR061988 · NIAMS · TUFTS UNIVERSITY MEDFORD · PI HUNG, CLARK T., KAPLAN, DAVID L. · 2011 to 2015
$3.3M
NIAMS NIH HHS R01 AR061988
6 · The paper itself

Abstract

Phase Contrast Microscopy (PCM) is an important tool for the long term study of living cells. Unlike fluorescence methods which suffer from photobleaching of fluorophore or dye molecules, PCM image contrast is generated by the natural variations in optical index of refraction. Unfortunately, the same physical principles which allow for these studies give rise to complex artifacts in the raw PCM imagery. Of particular interest in this paper are neuron images where these image imperfections manifest in very different ways for the two structures of specific interest: cell bodies (somas) and dendrites. To address these challenges, we introduce a novel parametric image model using the level set framework and an associated variational approach which simultaneously restores and segments this class of images. Using this technique as the basis for an automated image analysis pipeline, results for both the synthetic and real images validate and demonstrate the advantages of our approach.

Indexed as

(100.0100) Image processing(100.1830) Deconvolution(100.2960) Image analysis(100.3020) Image reconstruction-restoration(100.3190) Inverse problems

Identifiers

PMID26601004
PMCPMC4646548
OpenAlexW2297992998

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.