Cargando…

Mathematical morphology-based approach to the enhancement of morphological features in medical images

BACKGROUND: Medical image processing is essential in many fields of medical research and clinical practice because it greatly facilitates early and accurate detection and diagnosis of diseases. In particular, contrast enhancement is important for optimal image quality and visibility. This paper prop...

Descripción completa

Detalles Bibliográficos
Autor principal: Kimori, Yoshitaka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3275547/
https://www.ncbi.nlm.nih.gov/pubmed/22177340
http://dx.doi.org/10.1186/2043-9113-1-33
_version_ 1782223234425421824
author Kimori, Yoshitaka
author_facet Kimori, Yoshitaka
author_sort Kimori, Yoshitaka
collection PubMed
description BACKGROUND: Medical image processing is essential in many fields of medical research and clinical practice because it greatly facilitates early and accurate detection and diagnosis of diseases. In particular, contrast enhancement is important for optimal image quality and visibility. This paper proposes a new image processing method for enhancing morphological features of masses and other abnormalities in medical images. METHOD: The proposed method involves two steps: (1) selective extraction of target features by mathematical morphology and (2) enhancement of the extracted features by two contrast modification techniques. RESULTS: The goal of the proposed method is to enable enhancement of fine morphological features of a lesion region with high suppression of surrounding tissues. The effectiveness of the method was evaluated in quantitative terms of the contrast improvement ratio. The results clearly show that the method outperforms five conventional contrast enhancement methods. The effectiveness and usefulness of the proposed method were further demonstrated by application to three types of medical images: a mammographic image, a chest radiographic image, and a retinal image. CONCLUSION: The proposed method enables specific extraction and enhancement of mass lesions, which is essential for clinical diagnosis based on medical image analysis. Thus, the method can be expected to achieve automatic recognition of lesion location and quantitative analysis of legion morphology.
format Online
Article
Text
id pubmed-3275547
institution National Center for Biotechnology Information
language English
publishDate 2011
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-32755472012-02-13 Mathematical morphology-based approach to the enhancement of morphological features in medical images Kimori, Yoshitaka J Clin Bioinforma Methodology BACKGROUND: Medical image processing is essential in many fields of medical research and clinical practice because it greatly facilitates early and accurate detection and diagnosis of diseases. In particular, contrast enhancement is important for optimal image quality and visibility. This paper proposes a new image processing method for enhancing morphological features of masses and other abnormalities in medical images. METHOD: The proposed method involves two steps: (1) selective extraction of target features by mathematical morphology and (2) enhancement of the extracted features by two contrast modification techniques. RESULTS: The goal of the proposed method is to enable enhancement of fine morphological features of a lesion region with high suppression of surrounding tissues. The effectiveness of the method was evaluated in quantitative terms of the contrast improvement ratio. The results clearly show that the method outperforms five conventional contrast enhancement methods. The effectiveness and usefulness of the proposed method were further demonstrated by application to three types of medical images: a mammographic image, a chest radiographic image, and a retinal image. CONCLUSION: The proposed method enables specific extraction and enhancement of mass lesions, which is essential for clinical diagnosis based on medical image analysis. Thus, the method can be expected to achieve automatic recognition of lesion location and quantitative analysis of legion morphology. BioMed Central 2011-12-16 /pmc/articles/PMC3275547/ /pubmed/22177340 http://dx.doi.org/10.1186/2043-9113-1-33 Text en Copyright ©2011 Kimori; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology
Kimori, Yoshitaka
Mathematical morphology-based approach to the enhancement of morphological features in medical images
title Mathematical morphology-based approach to the enhancement of morphological features in medical images
title_full Mathematical morphology-based approach to the enhancement of morphological features in medical images
title_fullStr Mathematical morphology-based approach to the enhancement of morphological features in medical images
title_full_unstemmed Mathematical morphology-based approach to the enhancement of morphological features in medical images
title_short Mathematical morphology-based approach to the enhancement of morphological features in medical images
title_sort mathematical morphology-based approach to the enhancement of morphological features in medical images
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3275547/
https://www.ncbi.nlm.nih.gov/pubmed/22177340
http://dx.doi.org/10.1186/2043-9113-1-33
work_keys_str_mv AT kimoriyoshitaka mathematicalmorphologybasedapproachtotheenhancementofmorphologicalfeaturesinmedicalimages