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Probabilistic Multi-Compartment Deformable Model, Application to Cell Segmentation

Abstract

dc:description.abstract

A crucial task in computer vision and biomedical image applications is to represent images in a numerically compact form for understanding, evaluating and/or mining their content. The fundamental step of this task is the segmentation of images into regions, given some homogeneity criteria, prior appearance and/or shape information criteria. Specifically, segmentation of cells in microscopic images is the first step in analyzing many biomedical applications. This thesis is a part of the project entitled "Construction and profiling of biodegradable cardiac patches for the co-delivery of bFGF and G-CSF growth factors" funded by National Institutes of Health (NIH). We present a method that simultaneously segments the population of cells while partitioning the cell regions into cytoplasm and nucleus in order to evaluate the spatial coordination on the image plane, density and orientation of cells. Having static microscopic images, with no edge information of a cytoplasm boundary and no time sequence constraints, traditional cell segmentation methods would not perform well. The proposed method combines deformable models with a probabilistic framework in a simple graphical model such that it would capture the shape, structure and appearance of a cell. The process aims at the simultaneous cell partitioning into nucleus and cytoplasm. We considered the relative topology of the two distinct cell compartments to derive a better segmentation and compensate for the lack of edge information. The framework is applied to static fluorescent microscopy, where the cultured cells are stained with calcein AM.

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Farhand, Sepehr
Advisor dc:contributor.advisor
  • Tsechpenakis, Gavriil

Subjects

dc:subject × 4

Rights

Language dc:language.iso
en_US

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:scholarworks.indianapolis.iu.edu:1805/3359

Chain of custody

source
Harvested from
IUPUI
Base URL
scholarworks.indianapolis.iu.edu/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Farhand, Sepehr. Probabilistic Multi-Compartment Deformable Model, Application to Cell Segmentation. 2013. https://hdl.handle.net/1805/3359