Literature DB >> 33948761

Automatic Segmentation of Bone Canals in Histological Images.

Pedro Henrique Campos Cunha Gondim1, Pedro Henrique Justino Oliveira Limirio2, Flaviana Soares Rocha2, Jonas Dantas Batista2, Paula Dechichi3, Bruno Augusto Nassif Travençolo1, André Ricardo Backes4.   

Abstract

The literature provides many works that focused on cell nuclei segmentation in histological images. However, automatic segmentation of bone canals is still a less explored field. In this sense, this paper presents a method for automatic segmentation approach to assist specialists in the analysis of the bone vascular network. We evaluated the method on an image set through sensitivity, specificity and accuracy metrics and the Dice coefficient. We compared the results with other automatic segmentation methods (neighborhood valley emphasis (NVE), valley emphasis (VE) and Otsu). Results show that our approach is proved to be more efficient than comparable methods and a feasible alternative to analyze the bone vascular network.
© 2021. Society for Imaging Informatics in Medicine.

Entities:  

Keywords:  Artifact removal; Bone canal; Bone vascular network; Image segmentation; Mathematical morphology

Mesh:

Year:  2021        PMID: 33948761      PMCID: PMC8329125          DOI: 10.1007/s10278-021-00454-1

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.903


  10 in total

1.  Segmentation of histology slides of cortical bone using pulse coupled neural networks optimized by particle-swarm optimization.

Authors:  Ilige S Hage; Ramsey F Hamade
Journal:  Comput Med Imaging Graph       Date:  2013-08-31       Impact factor: 4.790

2.  A deep learning algorithm for one-step contour aware nuclei segmentation of histopathology images.

Authors:  Yuxin Cui; Guiying Zhang; Zhonghao Liu; Zheng Xiong; Jianjun Hu
Journal:  Med Biol Eng Comput       Date:  2019-07-26       Impact factor: 2.602

3.  Automated classification of oral premalignant lesions using image cytometry and Random Forests-based algorithms.

Authors:  Jonathan Baik; Qian Ye; Lewei Zhang; Catherine Poh; Miriam Rosin; Calum MacAulay; Martial Guillaud
Journal:  Cell Oncol (Dordr)       Date:  2014-05-10       Impact factor: 6.730

4.  Dose-dependent effect of radiation on titanium implants: a quantitative study in rabbits.

Authors:  Jun Yuan Li; Edmond Ho Nang Pow; Li Wu Zheng; Li Ma; Dora Lai Wan Kwong; Lim Kwong Cheung
Journal:  Clin Oral Implants Res       Date:  2013-02-18       Impact factor: 5.977

5.  Lymphoma images analysis using morphological and non-morphological descriptors for classification.

Authors:  Marcelo Zanchetta do Nascimento; Alessandro Santana Martins; Thaína Aparecida Azevedo Tosta; Leandro Alves Neves
Journal:  Comput Methods Programs Biomed       Date:  2018-05-31       Impact factor: 5.428

6.  Histological analysis of the alterations on cortical bone channels network after radiotherapy: A rabbit study.

Authors:  Gustavo Davi Rabelo; Marcelo Emílio Beletti; Paula Dechichi
Journal:  Microsc Res Tech       Date:  2010-10       Impact factor: 2.769

Review 7.  Methods for nuclei detection, segmentation, and classification in digital histopathology: a review-current status and future potential.

Authors:  Humayun Irshad; Antoine Veillard; Ludovic Roux; Daniel Racoceanu
Journal:  IEEE Rev Biomed Eng       Date:  2014

8.  Changes in cortical bone channels network and osteocyte organization after the use of zoledronic acid.

Authors:  Gustavo Davi Rabelo; Bruno Augusto Nassif Travençolo; Marcio Augusto Oliveira; Marcelo Emílio Beletti; Marina Gallottini; Fernando Ricardo Xavier da Silveira
Journal:  Arch Endocrinol Metab       Date:  2015-08-28       Impact factor: 2.309

9.  Dose-dependent effect of radiation on resorbable blast material titanium implants: an experimental study in rabbits.

Authors:  Gülnihal Emrem Doğan; Zekai Halici; Emre Karakus; Burak Erdemci; Akgün Alsaran; Irfan Cinar
Journal:  Acta Odontol Scand       Date:  2017-10-23       Impact factor: 2.331

10.  Automatic nuclei segmentation in H&E stained breast cancer histopathology images.

Authors:  Mitko Veta; Paul J van Diest; Robert Kornegoor; André Huisman; Max A Viergever; Josien P W Pluim
Journal:  PLoS One       Date:  2013-07-29       Impact factor: 3.240

  10 in total

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