A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

Multilevel space-time aggregation for bright field cell microscopy segmentation and tracking. | LitMetric

AI Article Synopsis

  • A multilevel aggregation technique, based on "Segmentation by Weighted Aggregation" and Algebraic Multigrid methods, is used to segment live cell images effectively.
  • A new "saliency measure" is introduced to determine when pixel groups form significant segments, addressing issues that arise from relying solely on multilevel intensity similarity for segmentation.
  • Preliminary results suggest that combining multilevel intensity variance with intensity similarity improves cell segmentation accuracy, and the method's potential for tracking individual cells in temporal image sequences is discussed for future applications.

Article Abstract

A multilevel aggregation method is applied to the problem of segmenting live cell bright field microscope images. The method employed is a variant of the so-called "Segmentation by Weighted Aggregation" technique, which itself is based on Algebraic Multigrid methods. The variant of the method used is described in detail, and it is explained how it is tailored to the application at hand. In particular, a new scale-invariant "saliency measure" is proposed for deciding when aggregates of pixels constitute salient segments that should not be grouped further. It is shown how segmentation based on multilevel intensity similarity alone does not lead to satisfactory results for bright field cells. However, the addition of multilevel intensity variance (as a measure of texture) to the feature vector of each aggregate leads to correct cell segmentation. Preliminary results are presented for applying the multilevel aggregation algorithm in space time to temporal sequences of microscope images, with the goal of obtaining space-time segments ("object tunnels") that track individual cells. The advantages and drawbacks of the space-time aggregation approach for segmentation and tracking of live cells in sequences of bright field microscope images are presented, along with a discussion on how this approach may be used in the future work as a building block in a complete and robust segmentation and tracking system.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2866245PMC
http://dx.doi.org/10.1155/2010/582760DOI Listing

Publication Analysis

Top Keywords

bright field
16
segmentation tracking
12
microscope images
12
space-time aggregation
8
multilevel aggregation
8
field microscope
8
multilevel intensity
8
multilevel
5
segmentation
5
multilevel space-time
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!