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

Kimori Y - J Clin Bioinforma (2011)

Bottom Line: 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.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Imaging Science Division, Center for Novel Science Initiatives, National Institutes of Natural Sciences, Toranomon 4-3-13, Minato-ku, Tokyo, 105-0001, Japan. y.kimori@nao.ac.jp.

ABSTRACT

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.

No MeSH data available.


Related in: MedlinePlus

Image enhancement achieved by the proposed method for a nodule in a chest radiographic image. (A) Original chest radiographic image (JPCLN044); the location of the single lesion (pulmonary nodule) is indicated by the arrow. (B) Enhanced image obtained by the proposed method.
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Figure 6: Image enhancement achieved by the proposed method for a nodule in a chest radiographic image. (A) Original chest radiographic image (JPCLN044); the location of the single lesion (pulmonary nodule) is indicated by the arrow. (B) Enhanced image obtained by the proposed method.

Mentions: Figure 6 shows the image enhancement achieved by the proposed method for a chest radiographic image (JPCLN044). In the original image (Figure 6(A), resized to 512 × 512 pixels, resolution 0.7 mm/pixel), the arrow points to the single lesion (pulmonary nodule). The nodule overlaps with a rib in the lung field. The enhanced image (Figure 6(B)) shows the nodule extracted with a line segment structuring element (length 31 pixels or 21.7 mm). The figure shows that the nodule is more clearly evident and the ribs and the surrounding lung parenchyma are suppressed.


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

Kimori Y - J Clin Bioinforma (2011)

Image enhancement achieved by the proposed method for a nodule in a chest radiographic image. (A) Original chest radiographic image (JPCLN044); the location of the single lesion (pulmonary nodule) is indicated by the arrow. (B) Enhanced image obtained by the proposed method.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3275547&req=5

Figure 6: Image enhancement achieved by the proposed method for a nodule in a chest radiographic image. (A) Original chest radiographic image (JPCLN044); the location of the single lesion (pulmonary nodule) is indicated by the arrow. (B) Enhanced image obtained by the proposed method.
Mentions: Figure 6 shows the image enhancement achieved by the proposed method for a chest radiographic image (JPCLN044). In the original image (Figure 6(A), resized to 512 × 512 pixels, resolution 0.7 mm/pixel), the arrow points to the single lesion (pulmonary nodule). The nodule overlaps with a rib in the lung field. The enhanced image (Figure 6(B)) shows the nodule extracted with a line segment structuring element (length 31 pixels or 21.7 mm). The figure shows that the nodule is more clearly evident and the ribs and the surrounding lung parenchyma are suppressed.

Bottom Line: 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.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Imaging Science Division, Center for Novel Science Initiatives, National Institutes of Natural Sciences, Toranomon 4-3-13, Minato-ku, Tokyo, 105-0001, Japan. y.kimori@nao.ac.jp.

ABSTRACT

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.

No MeSH data available.


Related in: MedlinePlus