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

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

doi:10.1371/journal.pone.0207908

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.

Highlights

Cell classification via image processing has recently gained interest from the point of view of building computer assisted diagnostic tools for hematological malignancies
We modified the multiphase level set formulation by utilizing statistical information of the four regions of interest (ROIs) in the image, i.e., nucleus, cytoplasm, unstained cells, and the background, wherein the four ROI were modeled via four-phases of two level sets
Since the work by Saeedizadeh et al [24] addresses the problem of plasma cell segmentation, its pipeline is tuned to this cell type

Summary

Introduction

Cell classification via image processing has recently gained interest from the point of view of building computer assisted diagnostic tools for hematological malignancies. The computer assisted image processing tools can evaluate morphological features that are not discernable with human eyes. PCSeg Tool: Plasma cell segmentation from microscopic images cells are unwanted regions for the purpose of plasma cell segmentation, we replaced unstained cell pixels with the background pixels. This is carried out by replacing intensity of pixels having values less than 120 in the H-channel with the background pixel intensity (Fig 2). Four probability maps of the entire image were created corresponding to each of the four phases of the level set (one each for their respective regions of interest, namely, nucleus, cytoplasm, unstained cells, and the background) as below: pðU0jOijÞ

Objectives

Methods

Results

Discussion

Conclusion