Evidence map›Paper›PMID 30540767›Full record

ArticlePloS one2018

PCSeg: Color model driven probabilistic multiphase level set based tool for plasma cell segmentation in multiple myeloma.

Anubha Gupta, Pramit Mallick, Ojaswa Sharma, Ritu Gupta, Rahul Duggal

Abstract read
In one paragraph

Article in PloS one, 2018. 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
–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

2 citing papers in PubMed.

  1. Article
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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.

Anubha GuptaSBILab, Department of ECE, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), New Delhi, India.ORCID 0000-0002-7752-1926
Pramit MallickDepartment of Computer Science, Courant Institute of Mathematical Sciences, New York University, New York City, New York, United States of America.
Ojaswa SharmaDepartment of CSE, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), New Delhi, India.
Ritu GuptaLaboratory Oncology Unit, Dr. B. R.A. IRCH, All India Institute of Medical Sciences (AIIMS), New Delhi, India.
Rahul DuggalSBILab, Department of ECE, Indraprastha Institute of Information Technology-Delhi (IIIT-Delhi), New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plasma cell segmentation is the first stage of a computer assisted automated diagnostic tool for multiple myeloma (MM). Owing to large variability in biological cell types, a method for one cell type cannot be applied directly on the other cell types. In this paper, we present PCSeg Tool for plasma cell segmentation from microscopic medical images. These images were captured from bone marrow aspirate slides of patients with MM. PCSeg has a robust pipeline consisting of a pre-processing step, the proposed modified multiphase level set method followed by post-processing steps including the watershed and circular Hough transform to segment clusters of cells of interest and to remove unwanted cells. Our modified level set method utilizes prior information about the probability densities of regions of interest (ROIs) in the color spaces and provides a solution to the minimal-partition problem to segment ROIs in one of the level sets of a two-phase level set formulation. PCSeg tool is tested on a number of microscopic images and provides good segmentation results on single cells as well as efficient segmentation of plasma cell clusters.

Indexed as

AlgorithmsDiagnosis, Computer-AssistedHumansImage Processing, Computer-AssistedMicroscopyMultiple MyelomaPattern Recognition, AutomatedPlasma CellsSoftware

Identifiers

PMID30540767
PMCPMC6291116

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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.