scholarly journals Medical images classification for skin cancer using quantitative image features with optical coherence tomography

2016 ◽  
Vol 09 (02) ◽  
pp. 1650003 ◽  
Author(s):  
Wei Gao ◽  
Valery P. Zakharov ◽  
Oleg O. Myakinin ◽  
Ivan A. Bratchenko ◽  
Dmitry N. Artemyev ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Skin Cancer ◽  
Basal Cell ◽  
Image Features ◽  
Skin Tumors ◽  
P Value ◽  
Optical Coherence ◽  
Quantitative Image ◽  
Basal Cell Carcinomas

Optical coherence tomography (OCT) is employed in the diagnosis of skin cancer. Particularly, quantitative image features extracted from OCT images might be used as indicators to classify the skin tumors. In the present paper, we investigated intensity-based, texture-based and fractal-based features for automatically classifying the melanomas, basal cell carcinomas and pigment nevi. Generalized estimating equations were used to test for differences between the skin tumors. A modified p value of [Formula: see text][Formula: see text]0.001 was considered statistically significant. Significant increase of mean and median of intensity and significant decrease of mean and median of absolute gradient were observed in basal cell carcinomas and pigment nevi as compared with melanomas. Significant decrease of contrast, entropy and fractal dimension was also observed in basal cell carcinomas and pigment nevi as compared with melanomas. Our results suggest that the selected quantitative image features of OCT images could provide useful information to differentiate basal cell carcinomas and pigment nevi from the melanomas. Further research is warranted to determine how this approach may be used to improve the classification of skin tumors.

How histological features of basal cell carcinomas influence image quality in optical coherence tomography

2011 ◽  
Vol 4 (7-8) ◽  
pp. 544-551 ◽  
Author(s):  
Mette Mogensen ◽  
Birgit M. Nürnberg ◽  
Lars Thrane ◽  
Thomas M. Jørgensen ◽  
Peter E. Andersen ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Image Quality ◽  
Basal Cell ◽  
Optical Coherence ◽  
Histological Features ◽  
Basal Cell Carcinomas

LIGHT-INDUCED FLUORESCENCE SPECTROSCOPY AND OPTICAL COHERENCE TOMOGRAPHY OF BASAL CELL CARCINOMA

2009 ◽  
Vol 02 (03) ◽  
pp. 261-268 ◽  
Author(s):  
EKATERINA BORISOVA ◽  
ELFRIDA CARSTEA ◽  
LUMINITA CRISTESCU ◽  
ELMIRA PAVLOVA ◽  
NIKOLAY HADJIOLOV ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Skin Cancer ◽  
Basal Cell Carcinoma ◽  
Fluorescence Spectroscopy ◽  
Cell Carcinoma ◽  
Basal Cell ◽  
Normal Skin ◽  
Biological Tissues ◽  
Skin Lesions ◽  
Optical Coherence

Many up-to-date optical techniques have been developed and applied recently in clinical practice for obtaining qualitatively and quantitatively new data from the investigated lesions. Due to their high sensitivity in detection of small changes, these techniques are widely used for detection of early changes in biological tissues. Light-induced fluorescence spectroscopy (LIFS) is one of the most promising techniques for early detection of cutaneous neoplasia. Increasing number of recent publications have suggested that optical coherence tomography (OCT) also has potential for non-invasive diagnosis of skin cancer. This recent work is a part of clinical trial procedure for introduction of LIFS technique into the common medical practice in National Oncological Medical Center in Bulgaria for diagnosis of non-melanoma skin cancer. We focus our attention here on basal cell carcinoma lesions and their specific features revealed by LIFS and OCT analysis. In this paper we prove the efficiency of using the combined LIFS-OCT method in skin lesions studies by integrating the complimentary qualities of each particular technique. For LIFS measurements several excitation sources, each emitting at 365, 385 and 405 nm maxima are applied. An associated microspectrometer detects in vivo the fluorescence signals from human skin. The main spectral features of the lesions and normal skin are discussed and their possible origins are indicated. OCT images are used to evaluate the lesion thickness, structure and severity stage, when possible. The obtained results could be used to develop a more complete picture of optical properties of these widely spread skin disorders. At the same time, our studies show that the combined LIFS-OCT method could be introduced in clinical algorithms for early tumor detection and differentiation between normal/benign/malignant skin lesions.

scholarly journals Diagnostic Value of Optical Coherence Tomography Image Features for Diagnosis of Basal Cell Carcinoma

2021 ◽  
Author(s):  
Fieke Adan ◽  
Klara Mosterd ◽  
Nicole W.J. Kelleners-Smeets ◽  
Patty J. Nelemans
Keyword(s):  
Optical Coherence Tomography ◽  
Basal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Basal Cell ◽  
Diagnostic Value ◽  
Image Features ◽  
Small Subset ◽  
Optical Coherence Tomography Image ◽  
Optical Coherence ◽  
Discriminative Ability

Optical coherence tomography (OCT) is a noninvasive diagnostic method. Numerous morphological OCT features have been described for diagnosis of basal cell carcinoma (BCC). In this study, we evaluate the diagnostic value of established features and we explore whether the use of a small set of features enables accurate discrimination between BCC and non-BCC lesions and between BCC subtypes. For each lesion, presence or absence of specific features was recorded. Histopathology was used as a gold standard. Diagnostic parameters were calculated for each feature and multivariate logistic regression analyses were performed to evaluate the loss in discriminative ability when using a small subset of features instead of all features that are characteristic for BCC according to literature. Results show that the use of a limited number of features allows for good discrimination of superficial BCC from non-superficial BCC and non-BCC lesions. The prevalence of BCC was 75.3% (225/299) and the proposed diagnostic algorithm enabled detection of 97.8% of BCC lesions (220/225). Subtyping without the need for biopsy was possible in 132 of 299 patients (44%) with a predictive value for presence of superficial BCC of 84.3% versus 98.8% for presence of non-superficial BCC.

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