Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Gupta, Anubha, Mallick, Pramit, Sharma, Ojaswa, Gupta, Ritu, Duggal, Rahul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6291116/
https://www.ncbi.nlm.nih.gov/pubmed/30540767
http://dx.doi.org/10.1371/journal.pone.0207908
_version_ 1783380206362296320
author Gupta, Anubha
Mallick, Pramit
Sharma, Ojaswa
Gupta, Ritu
Duggal, Rahul
author_facet Gupta, Anubha
Mallick, Pramit
Sharma, Ojaswa
Gupta, Ritu
Duggal, Rahul
author_sort Gupta, Anubha
collection PubMed
description 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.
format Online
Article
Text
id pubmed-6291116
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-62911162018-12-28 PCSeg: Color model driven probabilistic multiphase level set based tool for plasma cell segmentation in multiple myeloma Gupta, Anubha Mallick, Pramit Sharma, Ojaswa Gupta, Ritu Duggal, Rahul PLoS One Research Article 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. Public Library of Science 2018-12-12 /pmc/articles/PMC6291116/ /pubmed/30540767 http://dx.doi.org/10.1371/journal.pone.0207908 Text en © 2018 Gupta et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Gupta, Anubha
Mallick, Pramit
Sharma, Ojaswa
Gupta, Ritu
Duggal, Rahul
PCSeg: Color model driven probabilistic multiphase level set based tool for plasma cell segmentation in multiple myeloma
title PCSeg: Color model driven probabilistic multiphase level set based tool for plasma cell segmentation in multiple myeloma
title_full PCSeg: Color model driven probabilistic multiphase level set based tool for plasma cell segmentation in multiple myeloma
title_fullStr PCSeg: Color model driven probabilistic multiphase level set based tool for plasma cell segmentation in multiple myeloma
title_full_unstemmed PCSeg: Color model driven probabilistic multiphase level set based tool for plasma cell segmentation in multiple myeloma
title_short PCSeg: Color model driven probabilistic multiphase level set based tool for plasma cell segmentation in multiple myeloma
title_sort pcseg: color model driven probabilistic multiphase level set based tool for plasma cell segmentation in multiple myeloma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6291116/
https://www.ncbi.nlm.nih.gov/pubmed/30540767
http://dx.doi.org/10.1371/journal.pone.0207908
work_keys_str_mv AT guptaanubha pcsegcolormodeldrivenprobabilisticmultiphaselevelsetbasedtoolforplasmacellsegmentationinmultiplemyeloma
AT mallickpramit pcsegcolormodeldrivenprobabilisticmultiphaselevelsetbasedtoolforplasmacellsegmentationinmultiplemyeloma
AT sharmaojaswa pcsegcolormodeldrivenprobabilisticmultiphaselevelsetbasedtoolforplasmacellsegmentationinmultiplemyeloma
AT guptaritu pcsegcolormodeldrivenprobabilisticmultiphaselevelsetbasedtoolforplasmacellsegmentationinmultiplemyeloma
AT duggalrahul pcsegcolormodeldrivenprobabilisticmultiphaselevelsetbasedtoolforplasmacellsegmentationinmultiplemyeloma