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Differentiation of benign pigmented skin lesions with the aid of computer image analysis: a novel approach.

Choi JW, Park YW, Byun SY, Youn SW - Ann Dermatol (2013)

Bottom Line: In the aspect of texture, the surface of the nevus showed the highest contrast and correlation.Finally, the color segmented pattern of the nevus and lentigo was far more concentric than that of seborrheic keratosis.We found that the subtle distinctions between nevus, lentigo and seborrheic keratosis, which are likely to be unrecognized by ocular inspection, are well emphasized and detected with the aid of software.

View Article: PubMed Central - PubMed

Affiliation: Department of Dermatology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea.

ABSTRACT

Background: The differential diagnosis of common pigmented skin lesions is important in cosmetic dermatology. The computer aided image analysis would be a potent ancillary diagnostic tool when patients are hesitant to undergo a skin biopsy.

Objective: We investigated the numerical parameters discriminating each pigmented skin lesion from another with statistical significance.

Methods: For each of the five magnified digital images containing clinically diagnosed nevus, lentigo and seborrheic keratosis, a total of 23 parameters describing the morphological, color, texture and topological features were calculated with the aid of a self-developed image analysis software. A novel concept of concentricity was proposed, which represents how closely the color segmentation resembles a concentric circle.

Results: Morphologically, seborrheic keratosis was bigger and spikier than nevus and lentigo. The color histogram revealed that nevus was the darkest and had the widest variation in tone. In the aspect of texture, the surface of the nevus showed the highest contrast and correlation. Finally, the color segmented pattern of the nevus and lentigo was far more concentric than that of seborrheic keratosis.

Conclusion: We found that the subtle distinctions between nevus, lentigo and seborrheic keratosis, which are likely to be unrecognized by ocular inspection, are well emphasized and detected with the aid of software.

No MeSH data available.


Related in: MedlinePlus

Color segmented images of nevus and seborrheic keratosis. (A, E) Original gray images of nevus and seborrheic keratosis. (B, F) For nevus, it is well segmented as a concentric pattern through K-means algorithm, K=4. However, the segmented outcome is far from concentric for seborrheic keratosis. (C, G) Segment 1, of which pixels distribute most narrowly. For nevus, the pixels of segment 1 are well aggregated as a single piece. However, the pixels of segment 1 from seborrheic keratosis are relatively separated from each other. (D, H) Segment 2, of which pixels distribute second most narrowly. For nevus, it is a shape of a ring, while for seborrheic keratosis, it is a collection of separated pixel clusters. (I, M) Core, which is defined as the minimal convex area completely encircling segment 1. (J, N) Hull, which is defined as a minimal convex area completely encircling segment 2. (K, O) In the intersection of segment 1 and the hull of nevus, most pixels of segment 1 are located inside of the hull. Thus, the core inclusion (CI) is high (CI=1.0). However, the intersection of segment 1 and core is quite smaller than segment 1 (CI=0.690) for seborrheic keratosis. (L, P) The intersections of segment 2 and core. In the image for nevus, only few pixels of segment 2 overlap with the core. Thus, the hull exclusion (HE) is high (HE=0.952). However, for seborrheic keratosis, most pixels of segment 2 overlap with the core. Thus, HE is lower than that of nevus and lentigo (HE=0.109).
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Figure 4: Color segmented images of nevus and seborrheic keratosis. (A, E) Original gray images of nevus and seborrheic keratosis. (B, F) For nevus, it is well segmented as a concentric pattern through K-means algorithm, K=4. However, the segmented outcome is far from concentric for seborrheic keratosis. (C, G) Segment 1, of which pixels distribute most narrowly. For nevus, the pixels of segment 1 are well aggregated as a single piece. However, the pixels of segment 1 from seborrheic keratosis are relatively separated from each other. (D, H) Segment 2, of which pixels distribute second most narrowly. For nevus, it is a shape of a ring, while for seborrheic keratosis, it is a collection of separated pixel clusters. (I, M) Core, which is defined as the minimal convex area completely encircling segment 1. (J, N) Hull, which is defined as a minimal convex area completely encircling segment 2. (K, O) In the intersection of segment 1 and the hull of nevus, most pixels of segment 1 are located inside of the hull. Thus, the core inclusion (CI) is high (CI=1.0). However, the intersection of segment 1 and core is quite smaller than segment 1 (CI=0.690) for seborrheic keratosis. (L, P) The intersections of segment 2 and core. In the image for nevus, only few pixels of segment 2 overlap with the core. Thus, the hull exclusion (HE) is high (HE=0.952). However, for seborrheic keratosis, most pixels of segment 2 overlap with the core. Thus, HE is lower than that of nevus and lentigo (HE=0.109).

Mentions: The HE describes how exclusively the hull surrounds the core. The HE of a perfect concentric figure is one. However, if the first and second largest areas are intermixed with each other, the HE would be zero. To emphasize the discriminating power of those concentricity properties, the product of the three variables is defined as the concentricity ranging from zero to one. Of course, concentricity closer to one implies a better concentric structure. Actual examples of nevus and seborrheic keratosis are also supplied (Fig. 4).


Differentiation of benign pigmented skin lesions with the aid of computer image analysis: a novel approach.

Choi JW, Park YW, Byun SY, Youn SW - Ann Dermatol (2013)

Color segmented images of nevus and seborrheic keratosis. (A, E) Original gray images of nevus and seborrheic keratosis. (B, F) For nevus, it is well segmented as a concentric pattern through K-means algorithm, K=4. However, the segmented outcome is far from concentric for seborrheic keratosis. (C, G) Segment 1, of which pixels distribute most narrowly. For nevus, the pixels of segment 1 are well aggregated as a single piece. However, the pixels of segment 1 from seborrheic keratosis are relatively separated from each other. (D, H) Segment 2, of which pixels distribute second most narrowly. For nevus, it is a shape of a ring, while for seborrheic keratosis, it is a collection of separated pixel clusters. (I, M) Core, which is defined as the minimal convex area completely encircling segment 1. (J, N) Hull, which is defined as a minimal convex area completely encircling segment 2. (K, O) In the intersection of segment 1 and the hull of nevus, most pixels of segment 1 are located inside of the hull. Thus, the core inclusion (CI) is high (CI=1.0). However, the intersection of segment 1 and core is quite smaller than segment 1 (CI=0.690) for seborrheic keratosis. (L, P) The intersections of segment 2 and core. In the image for nevus, only few pixels of segment 2 overlap with the core. Thus, the hull exclusion (HE) is high (HE=0.952). However, for seborrheic keratosis, most pixels of segment 2 overlap with the core. Thus, HE is lower than that of nevus and lentigo (HE=0.109).
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Related In: Results  -  Collection

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Figure 4: Color segmented images of nevus and seborrheic keratosis. (A, E) Original gray images of nevus and seborrheic keratosis. (B, F) For nevus, it is well segmented as a concentric pattern through K-means algorithm, K=4. However, the segmented outcome is far from concentric for seborrheic keratosis. (C, G) Segment 1, of which pixels distribute most narrowly. For nevus, the pixels of segment 1 are well aggregated as a single piece. However, the pixels of segment 1 from seborrheic keratosis are relatively separated from each other. (D, H) Segment 2, of which pixels distribute second most narrowly. For nevus, it is a shape of a ring, while for seborrheic keratosis, it is a collection of separated pixel clusters. (I, M) Core, which is defined as the minimal convex area completely encircling segment 1. (J, N) Hull, which is defined as a minimal convex area completely encircling segment 2. (K, O) In the intersection of segment 1 and the hull of nevus, most pixels of segment 1 are located inside of the hull. Thus, the core inclusion (CI) is high (CI=1.0). However, the intersection of segment 1 and core is quite smaller than segment 1 (CI=0.690) for seborrheic keratosis. (L, P) The intersections of segment 2 and core. In the image for nevus, only few pixels of segment 2 overlap with the core. Thus, the hull exclusion (HE) is high (HE=0.952). However, for seborrheic keratosis, most pixels of segment 2 overlap with the core. Thus, HE is lower than that of nevus and lentigo (HE=0.109).
Mentions: The HE describes how exclusively the hull surrounds the core. The HE of a perfect concentric figure is one. However, if the first and second largest areas are intermixed with each other, the HE would be zero. To emphasize the discriminating power of those concentricity properties, the product of the three variables is defined as the concentricity ranging from zero to one. Of course, concentricity closer to one implies a better concentric structure. Actual examples of nevus and seborrheic keratosis are also supplied (Fig. 4).

Bottom Line: In the aspect of texture, the surface of the nevus showed the highest contrast and correlation.Finally, the color segmented pattern of the nevus and lentigo was far more concentric than that of seborrheic keratosis.We found that the subtle distinctions between nevus, lentigo and seborrheic keratosis, which are likely to be unrecognized by ocular inspection, are well emphasized and detected with the aid of software.

View Article: PubMed Central - PubMed

Affiliation: Department of Dermatology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea.

ABSTRACT

Background: The differential diagnosis of common pigmented skin lesions is important in cosmetic dermatology. The computer aided image analysis would be a potent ancillary diagnostic tool when patients are hesitant to undergo a skin biopsy.

Objective: We investigated the numerical parameters discriminating each pigmented skin lesion from another with statistical significance.

Methods: For each of the five magnified digital images containing clinically diagnosed nevus, lentigo and seborrheic keratosis, a total of 23 parameters describing the morphological, color, texture and topological features were calculated with the aid of a self-developed image analysis software. A novel concept of concentricity was proposed, which represents how closely the color segmentation resembles a concentric circle.

Results: Morphologically, seborrheic keratosis was bigger and spikier than nevus and lentigo. The color histogram revealed that nevus was the darkest and had the widest variation in tone. In the aspect of texture, the surface of the nevus showed the highest contrast and correlation. Finally, the color segmented pattern of the nevus and lentigo was far more concentric than that of seborrheic keratosis.

Conclusion: We found that the subtle distinctions between nevus, lentigo and seborrheic keratosis, which are likely to be unrecognized by ocular inspection, are well emphasized and detected with the aid of software.

No MeSH data available.


Related in: MedlinePlus