Characterization of skin lesion texture in diffuse reflectance spectroscopic images

This paper examines various texture features extracted from skin lesion images obtained by using diffuse reflectance spectroscopic imaging. Different image texture features have been applied to such images to separate precancerous from benign cases. These features are extracted based on the co-occurrence matrix, wavelet decomposition , fractal signature, and granulometric approaches. The results so far indicate that fractal and wavelet-based features are effective in distinguishing precancerous from benign cases

Characterization of skin lesion texture in diffuse reflectance spectroscopic images

This paper examines various texture features extracted from skin lesion images obtained by using diffuse reflectance spectroscopic imaging. Different image texture features have been applied to such images to separate precancerous from benign cases. These features are extracted based on the co-occurrence matrix, wavelet decomposition , fractal signature, and granulometric approaches. The results so far indicate that fractal and wavelet-based features are effective in distinguishing precancerous from benign cases

Skin lesion classification using oblique-incidence diffuse reflectance spectroscopic imaging

We discuss the use of a noninvasive in vivo optical technique, diffuse reflectance spectroscopic imaging with oblique incidence, to distinguish between benign and cancer-prone skin lesions. Various image features were examined to classify the images from lesions into benign and cancerous categories. Two groups of lesions were processed separately: Group 1 includes keratoses, warts versus carcinomas; and group 2 includes common nevi versus dysplastic nevi. A region search algorithm was developed to extract both one- and two-dimensional spectral information. A bootstrap-based Bayes classifier was used for classification. A computer-assisted tool was then devised to act as an electronic second opinion to the dermatologist. Our approach generated only one false-positive misclassification out of 23 cases collected for group 1 and two misclassifications out of 34 cases collected for group 2 under the worst estimation condition

Multi-spectral light interaction modeling and imaging of skin lesions

Nevoscope as a diagnostic tool for melanoma was evaluated using a white light source with promising results. Information about the lesion depth and its structure will further improve the sensitivity and specificity of melanoma diagnosis. Wavelength-dependent variable penetration power of monochromatic light in the trans-illumination imaging using the Nevoscope can be used to obtain this information. Optimal selection of wavelengths for multi-spectral imaging requires light-tissue interaction modeling. For this, three-dimensional wavelength dependent voxel-based models of skin lesions with different depths are proposed. A Monte Carlo simulation algorithm (MCSVL) is developed in MATLAB and the tissue models are simulated using the Nevoscope optical geometry. 350-700nm optical wavelengths with an interval of 5nm are used in the study. A correlation analysis between the lesion depth and the diffuse reflectance is then used to obtain wavelengths that will produce diffuse reflectance suitable for imaging and give information related to the nevus depth and structure. Using the selected wavelengths, multi-spectral trans-illumination images of the skin lesions are collected and analyzed. An adaptive wavelet transform based tree-structure classification method (ADWAT) is proposed to classify epi-illuminance images of the skin lesions obtained using a white light source into melanoma and dysplastic nevus images classes. In this method, tree-structure models of melanoma and dysplastic nevus are developed and semantically compared with the tree-structure of the unknown image for classification. Development of the tree-structure is dependent on threshold selections obtained from a statistical analysis of the feature set. This makes the classification method adaptive. The true positive value obtained for this classifier is 90% with a false positive of 10%. The Extended ADWAT method and Fuzzy Membership Functions method using combined features from the epi-illuminance and multi-spectral images further improve the sensitivity and specificity of melanoma diagnosis. The combined feature set with the Extended-ADWAT method gives a true positive of 93.33% with a false positive of 8.88%. The Gaussian Membership Functions give a true positive of 100% with a false positive of 17.77% while the Bell Membership Functions give a true positive of 100% with a false positive of 4.44%

Skin lesion classification using oblique-incidence diffuse reflectance spectroscopic imaging

We discuss the use of a noninvasive in vivo optical technique, diffuse reflectance spectroscopic imaging with oblique incidence, to distinguish between benign and cancer-prone skin lesions. Various image features were examined to classify the images from lesions into benign and cancerous categories. Two groups of lesions were processed separately: Group 1 includes keratoses, warts versus carcinomas; and group 2 includes common nevi versus dysplastic nevi. A region search algorithm was developed to extract both one- and two-dimensional spectral information. A bootstrap-based Bayes classifier was used for classification. A computer-assisted tool was then devised to act as an electronic second opinion to the dermatologist. Our approach generated only one false-positive misclassification out of 23 cases collected for group 1 and two misclassifications out of 34 cases collected for group 2 under the worst estimation condition

Multimodal snapshot spectral imaging for oral cancer diagnostics: a pilot study

Optical imaging and spectroscopy have emerged as effective tools for detecting malignant changes associated with oral cancer. While clinical studies have demonstrated high sensitivity and specificity for detection, current devices either interrogate a small region or can have reduced performance for some benign lesions. We describe a snapshot imaging spectrometer that combines the large field-of-view of widefield imaging with the diagnostic strength of spectroscopy. The portable device can stream RGB images at 7.2 frames per second and record both autofluorescence and reflectance spectral datacubes in < 1 second. We report initial data from normal volunteers and oral cancer patients

Raman spectroscopy and diffuse reflectance spectroscopy for diagnosis of human cancer and acanthosis nigricans

Cancer and diabetes are common chronic diseases in today\u27s world causing numerous deaths in adults as well as children. Most common types of cancers in adults include prostate, lung, breast, colorectal and head and neck squamous cell carcinoma, while among children; leukemia, and brain and central nervous system cancers are quite common. In each of these cases, early detection of the cancer or disease dramatically increases the chances of successful treatment. In recent years, there has been much interest in using Raman spectroscopy and diffuse reflectance spectroscopy as analytical optical spectroscopic methods for early diagnosis of diseases. Raman spectroscopy can be used to measure changes in the bio-molecular composition of a tissue specimen, and diffuse reflectance spectroscopy can measure chromophores of the skin. In this research, archived (formalin-fixed paraffin processed) tissues of head and neck squamous cell carcinoma, prostate, and pediatric tumors have been investigated using Raman spectroscopy. We have utilized statistical methods such as principal component analysis (PCA) and discriminant function analysis (DFA) to analyze the spectral output and distinguish between normal and cancerous tissues. The results show cancerous tissues can be successfully distinguished from normal tissues in three cancer types in ex vivo. However, due to loss of biochemical in the tissue processing (paraffinizing and deparaffinizing procedure), the prediction ability of the archived tissues are less compared to frozen tissues as observed in the pediatric tumor investigation. We also investigated the diagnostic capability of diffuse reflectance spectroscopy and colorimetry on a skin disease, acanthosis nigricans in vivo. The aim is to quantify and characterize the skin color change associated with acanthosis nigricans skin disease in insulin-resistant obese individuals. We observe both the instruments can be utilized to detect acanthosis nigricans with more than 87% sensitivity and 94% specificity when combined with advanced chemometric methods

Early detection of curable precancerous lesions in the oral cavity using polarized reflectance spectroscopy

textIn 2004, the American Cancer Society estimates that more than 1,500 deaths a day associated with cancer will occur. For all cancers, the five-year survival rate is greater if diagnosis is made at an early stage of cancer development. The focus of this dissertation is on the development of a highly selective and sensitive non-invasive optical device for the early detection of epithelial precancers, which has enormous potential to reduce patient morbidity and mortality. Specifically, this dissertation will concentrate on the assessment of the polarized reflectance spectroscopy (PRS) to detect and diagnose early curable precancerous lesions within the oral cavity. PRS is a variation of elastic scattering spectroscopy which is sensitive to important morphological indicators of early precancer, such as scatterer size and refractive index. In this dissertation I will present a fiber optic probe that combines polarized illumination and detection with an angled distal probe geometry to detect the size dependent scattering within the epithelial layer of tissue, where most cancer originate. This technique allows a simple Mie theory based model to be used to extract the nuclear sizes. Tissue phantoms that mimic the two-layered scattering structure of mucosal tissue were used to test the feasibility of PRS to extract scatter sizes. Results of these studies showed excellent agreement between spectroscopically derived scatter sizes and direct microscopy measurements. In vivo measurements within the oral cavity of normal volunteers also yielded nuclear sizes that corresponded very well to published values. The PRS device was found to be capable of discriminating normal oral mucosa tissue from severe dysplasia in a collaborative pilot clinical trial of 21 patients, at the UT MD Anderson Cancer Center. Nuclear morphology extracted from the polarized spectroscopy measurements compared very well to quantitative histopathology. Overall this dissertation gives a thorough basis for a larger statistically significant clinical trial to be performed to determine the sensitivity and specificity of polarized reflectance spectroscopy as a screening and diagnostic instrument in the oral cavity. The work in this dissertation lays the foundation for future exploration of the optical scattering properties polarized light within tissue for clinical applications.Physic