REGISTRATION AND COLOR CALIBRATION FOR DERMOSCOPY IMAGES IN TIME-COURSE ANALYSIS

In this study, we proposed a fully automated image registration and color calibration method between time-course dermoscopy images only with observed images.We confirmed that the pro-posed method was effective to compensate both geometrical and hronological changes between dermoscopy images in the time-course analysis. Our proposed algorithm aligned the time-course images with a precision of 93.7 ± 4.8,% and a recall of 95.8 ± 4.1%, respectively. Our color calibra-tion method largely reduced the color difference between time-course images ∆E from 11.8 ± 6.4 to 4.6 ± 1.4

Visible and extended near-infrared multispectral imaging for skin cancer diagnosis

With the goal of diagnosing skin cancer in an early and noninvasive way, an extended near infrared multispectral imaging system based on an InGaAs sensor with sensitivity from 995 nm to 1613 nm was built to evaluate deeper skin layers thanks to the higher penetration of photons at these wavelengths. The outcomes of this device were combined with those of a previously developed multispectral system that works in the visible and near infrared range (414 nm⁻995 nm). Both provide spectral and spatial information from skin lesions. A classification method to discriminate between melanomas and nevi was developed based on the analysis of first-order statistics descriptors, principal component analysis, and support vector machine tools. The system provided a sensitivity of 78.6% and a specificity of 84.6%, the latter one being improved with respect to that offered by silicon sensors

Visible and extended near-infrared multispectral imaging for skin cancer diagnosis

Postprint (published version

Doctor of Philosophy

dissertationUsing eye-tracking technology to capture the visual scanpaths of a sample of laypersons (N = 92), the current study employed a 2 (training condition: ABCDE vs. Ugly Duckling Sign) Ã- 2 (visual condition: photorealistic images vs. illustrations) factorial design to assess whether SSE training succeeds or fails in facilitating increases in sensitivity and specificity. Self-efficacy and perceived importance were tested as moderators, and eye-tracking fixation metrics as mediators, within the framework of Visual Skill Acquisition Theory (VSAT). For sensitivity, results indicated a significant main effect for visual condition, F(1,88) = 7.102, p = .009, wherein illustrations (M = .524, SD = .197) resulted in greater sensitivity than photos (M = .425, SD = .159, d = .55). For specificity, the main effect for training was not significant, F(1,88) = 2.120, p = .149; however, results indicated a significant main effect for visual condition, F(1,88) = 4.079, p = .046, wherein photos (M = .821, SD = .108) resulted in greater specificity than illustrations (M = .770, SD = .137, d = .41). The interaction for training Ã- visual condition, F(1,88) = 3.554, p = .063, was significant within a 90% confidence interval, such that those within the UDS Photo condition displayed greater specificity than all other combinations of training and visual condition. No significant moderated mediation manifested for sensitivity, but for specificity, the model was significant, r = .59, R2 = .34, F(9,82) = 4.7783, p =.001, with Percent of Time in Lookzone serving as a significant mediator, and both self-efficacy and visual condition significantly moderating the mediation. For those in the photo condition with very high self-efficacy, UDS increased specificity directly. For those in the photo condition with self-efficacy levels at the mean or lower, there was a conditional indirect effect through Percent of Time in Lookzoneâ€"which is to say that these individuals spent a larger amount of their viewing time on target (observing the atypical nevi)â€"and time on target is positively related to specificity. Findings suggest that existing SSE training techniques may be enhanced by maximizing visual processing efficiency

Towards the early detection of melanoma by automating the measurement of asymmetry, border irregularity, color variegation, and diameter in dermoscopy images

The incidence of melanoma, the most aggressive form of skin cancer, has increased more than many other cancers in recent years. The aim of this thesis is to develop objective measures and automated methods to evaluate the ABCD (Asymmetry, Border irregularity, Color variegation, and Diameter) rule features in dermoscopy images, a popular method that provides a simple means for appraisal of pigmented lesions that might require further investigation by a specialist. However, research gaps in evaluating those features have been encountered in literature. To extract skin lesions, two segmentation approaches that are robust to inherent dermoscopic image problems have been proposed, and showed to outperform other approaches used in literature. Measures for finding asymmetry and border irregularity have been developed. The asymmetry measure describes invariant features, provides a compactness representation of the image, and captures discriminative properties of skin lesions. The border irregularity measure, which is preceded by a border detection step carried out by a novel edge detection algorithm that represents the image in terms of fuzzy concepts, is rotation invariant, characterizes the complexity of the shape associated with the border, and robust to noise. To automate the measures, classification methods that are based on ensemble learning and which take the ambiguity of data into consideration have been proposed. Color variegation was evaluated by determining the suspicious colors of melanoma from a generated color palette for the image, and the diameter of the skin lesion was measured using a shape descriptor that was eventually represented in millimeters. The work developed in the thesis reflects the automatic dermoscopic image analysis standard pipeline, and a computer-aided diagnosis system (CAD) for the automatic detection and objective evaluation of the ABCD rule features. It can be used as an objective bedside tool serving as a diagnostic adjunct in the clinical assessment of skin lesions

Development of a new spectral imaging system for the diagnosis of skin cancer

The incidence of skin cancer in Europe, US and Australia has been rising rapidly. Skin cancer accounts for one in three cancers worldwide and a person has 1:25 chance to develop a melanoma, the most aggressive form. Visual inspection followed by histological examination is, still today, the gold standard for clinicians, which is carried out through a dermoscope, a handheld device with a magnifying lens and a white and uniform illumination field. The dermoscopic technique requires considerable training in the interpretation of what is seen and is highly dependent on subjective impressions. In consequence, a large number of unnecessary surgical procedures are performed. For this reason, in this thesis a spectral imaging system to improve skin cancer diagnosis has been developed. This work has been carried out in the framework of the European project DIAGNOPTICS "Diagnosis of skin cancer using optics", which aimed to launch a hospital service based on a multiphotonic platform to improve skin cancer with the combination of four non-invasive novel techniques: 3D and multispectral imaging, optical feedback interferometry and confocal microscopy. The handheld system built included a monochromatic CCD camera attached to an objective lens and a light source containing 32 light emitting diodes (LEDs) with 8 spectral bands from 400 nm to 1000 nm. An acquisition software to control all the components of the multispectral system was programmed as well as a simplest version for physicians. The changes over time of the emission of the LEDs was analysed, and also the linear response of the camera at each wavelength, the uniformity of the LED emission and the short and long-term repeatability of the system in acquiring images, to ensure the good performance of the system. In order to proceed with the Ethical Committee approval and to launch the systems in both hospitals, irradiance and radiance measurements were done according to the standard UNE-EN 62471. A Graphical User Interface (GUI) was developed for the spectral images processing and corresponding analysis, allowing spectral and colorimetric features to be computed in terms of reflectance, absorbance and colour parameters. Furthermore, a segmentation algorithm was also implemented to extract the isolated information from the lesion. For all images calculated in terms of any of the parameters, conventional statistical descriptors were obtained. As a first approach to extracting textural information we also used the analysis of the statistical properties of the histogram. An inclusion criteria and a measurement protocol were established. From all lesions analysed, 620 were measured with the multispectral system, 572 of them had a clinical or histopathological diagnosis, and 502 could be properly segmented. Therefore, 429 skin lesions were finally included in the study: 290 nevi, 95 melanomas and 44 basal cell carcinomas. A classification algorithm was developed in order to decide whether the lesions were malignant (melanomas and basal cell carcinomas) or not (nevi), splitting previously the data into training and validations set of the same size. 15 parameters from 1309 were found to be not redundant providing a 91.3% of sensitivity and 54.5% of specificity. Accordingly, the addition of textural information was shown to be useful for the diagnosis of malignant lesions than the sole use of averaged spectral and colour information. The same steps were carried out for the 3D imaging system also included in the multiphotonic platform. In this case, 3 parameters were found to be useful for the classification providing values of 55.6% and 83.7% of sensitivity and specificity, respectively. Finally, the combination of both system was also tested as a first attempt to improve the detection of melanomas, providing 100% and 72.2% of sensitivity and specificity, respectively. However, the conclusions reached in this case should be taken with caution due to the limited number of lesions.La incidència del càncer de pell a Europa, Estats Units i Austràlia ha anat augmentant ràpidament. Representa un de cada tres càncers a tot el món i una persona té 1:25 oportunitats de desenvolupar un melanoma, la forma més agressiva. Actualment, la inspecció visual amb un dermoscopi seguida d'un examen histològic és l'estàndard utilitzat pels metges a l'hora de diagnosticar-lo. La dermoscòpia requereix una formació considerable per interpretar el que es veu i depèn de les impressions subjectives dels clínics. En conseqüència, es realitzen una gran quantitat de procediments quirúrgics innecessaris. Per aquest motiu, en aquesta tesi s'ha desenvolupat una sistema d'imatge espectral per millorar el diagnòstic del càncer de pell. Aquest treball s'ha realitzat dins el marc del projecte Europeu DIAGNOPTICS ¿Diagnosis del càncer de pell utilitzant òptica?, el qual ha posat a punt un servei hospitalari basat en un plataforma multifotònica que combina quatre tècniques òptiques innovadores: sistemes d'imatge multiespectral 3D, interferometria de retroalimentació i microscòpia confocal. El sistema portàtil desenvolupat inclou una càmera monocromàtica CCD, un objectiu i una font de llum formada per 32 díodes emissors de llum (LED) amb 8 bandes espectrals diferents que emeten des de 400 nm fins a 1000 nm. S'ha preparat un programa d'adquisició per controlar tots els components del sistema així com una versió més simple del mateix pels metges. Per tal d'assegurar el bon funcionament del sistema, es van analitzar els canvis temporals en l'emissió dels LEDs així com la seva uniformitat d'emissió, la resposta lineal de la càmera per cada longitud d'ona i la repetibilitat del sistema pel què fa a l'adquisició d'imatges. Per tal d'obtenir l'aprovació del Comitè Ètic i poder realitzar l'estudi clínic en els hospitals, es van dur a terme mesures d'irradiància i radiància d'acord amb la norma UNE-EN 62471. També es va implementar una interfície gràfica d'usuari (GUI) per al processament de les imatges espectrals i la seva corresponent anàlisi. Aquest algorisme permet calcular paràmetres espectrals i colorimètrics de la pell en termes de reflectància, absorbància i d'altres basats en el color. A més, inclús es va desenvolupar un algorisme de segmentació per extreure informació aïllada de cada lesió. Per a totes les imatges calculades en termes de qualsevol paràmetre, es van obtenir descriptors estadístics convencionals i també es van utilitzar propietats estadístiques dels histogrames com una primera aproximació d'extreure informació de textura de la lesió. Finalment, es van establir els criteris d'inclusió i un protocol de mesura. De totes les lesions analitzades, se'n van mesurar 620, de les quals 572 tenien un diagnòstic clínic o histopatològic; 502 es van poder segmentar adequadament. D'aquesta manera es van incloure 429 lesions cutànies a l'estudi: 290 nevus, 95 melanomes i 44 carcinomes de cèl·lules basals. Es va desenvolupar un algorisme de classificació per determinar si les lesions eren malignes (melanomes i carcinomes de cèl·lules basals) o no (nevus), dividint prèviament les dades en un grup d'entrenament i un altre de validació de la mateixa mida. Es va observar que 15 del 1309 paràmetres proporcionaven informació rellevant per a la classificació, obtenint una sensibilitat del 91,3% i una especificitat del 54,5%. Així doncs, es demostra que la incorporació d'informació de textura és molt útil per al diagnòstic del càncer de pell més enllà de la informació espectral i de color. Aquests mateixos passos es van seguir pel sistema 3D també inclòs en la plataforma multifotònica, tot i que en aquest cas el número de lesions de què es disposava era més limitat. En aquest cas, es van seleccionar 3 paràmetres i es va obtenir una sensibilitat del 55,6% i una especificitat del 83,7%. Finalment, amb la combinació d'ambdós sistemes la sensibilitat obtinguda va ser de100% i l'especificitat del 72,2%.Postprint (published version

Development of a new spectral imaging system for the diagnosis of skin cancer

The incidence of skin cancer in Europe, US and Australia has been rising rapidly. Skin cancer accounts for one in three cancers worldwide and a person has 1:25 chance to develop a melanoma, the most aggressive form. Visual inspection followed by histological examination is, still today, the gold standard for clinicians, which is carried out through a dermoscope, a handheld device with a magnifying lens and a white and uniform illumination field. The dermoscopic technique requires considerable training in the interpretation of what is seen and is highly dependent on subjective impressions. In consequence, a large number of unnecessary surgical procedures are performed. For this reason, in this thesis a spectral imaging system to improve skin cancer diagnosis has been developed. This work has been carried out in the framework of the European project DIAGNOPTICS "Diagnosis of skin cancer using optics", which aimed to launch a hospital service based on a multiphotonic platform to improve skin cancer with the combination of four non-invasive novel techniques: 3D and multispectral imaging, optical feedback interferometry and confocal microscopy. The handheld system built included a monochromatic CCD camera attached to an objective lens and a light source containing 32 light emitting diodes (LEDs) with 8 spectral bands from 400 nm to 1000 nm. An acquisition software to control all the components of the multispectral system was programmed as well as a simplest version for physicians. The changes over time of the emission of the LEDs was analysed, and also the linear response of the camera at each wavelength, the uniformity of the LED emission and the short and long-term repeatability of the system in acquiring images, to ensure the good performance of the system. In order to proceed with the Ethical Committee approval and to launch the systems in both hospitals, irradiance and radiance measurements were done according to the standard UNE-EN 62471. A Graphical User Interface (GUI) was developed for the spectral images processing and corresponding analysis, allowing spectral and colorimetric features to be computed in terms of reflectance, absorbance and colour parameters. Furthermore, a segmentation algorithm was also implemented to extract the isolated information from the lesion. For all images calculated in terms of any of the parameters, conventional statistical descriptors were obtained. As a first approach to extracting textural information we also used the analysis of the statistical properties of the histogram. An inclusion criteria and a measurement protocol were established. From all lesions analysed, 620 were measured with the multispectral system, 572 of them had a clinical or histopathological diagnosis, and 502 could be properly segmented. Therefore, 429 skin lesions were finally included in the study: 290 nevi, 95 melanomas and 44 basal cell carcinomas. A classification algorithm was developed in order to decide whether the lesions were malignant (melanomas and basal cell carcinomas) or not (nevi), splitting previously the data into training and validations set of the same size. 15 parameters from 1309 were found to be not redundant providing a 91.3% of sensitivity and 54.5% of specificity. Accordingly, the addition of textural information was shown to be useful for the diagnosis of malignant lesions than the sole use of averaged spectral and colour information. The same steps were carried out for the 3D imaging system also included in the multiphotonic platform. In this case, 3 parameters were found to be useful for the classification providing values of 55.6% and 83.7% of sensitivity and specificity, respectively. Finally, the combination of both system was also tested as a first attempt to improve the detection of melanomas, providing 100% and 72.2% of sensitivity and specificity, respectively. However, the conclusions reached in this case should be taken with caution due to the limited number of lesions.La incidència del càncer de pell a Europa, Estats Units i Austràlia ha anat augmentant ràpidament. Representa un de cada tres càncers a tot el món i una persona té 1:25 oportunitats de desenvolupar un melanoma, la forma més agressiva. Actualment, la inspecció visual amb un dermoscopi seguida d'un examen histològic és l'estàndard utilitzat pels metges a l'hora de diagnosticar-lo. La dermoscòpia requereix una formació considerable per interpretar el que es veu i depèn de les impressions subjectives dels clínics. En conseqüència, es realitzen una gran quantitat de procediments quirúrgics innecessaris. Per aquest motiu, en aquesta tesi s'ha desenvolupat una sistema d'imatge espectral per millorar el diagnòstic del càncer de pell. Aquest treball s'ha realitzat dins el marc del projecte Europeu DIAGNOPTICS ¿Diagnosis del càncer de pell utilitzant òptica?, el qual ha posat a punt un servei hospitalari basat en un plataforma multifotònica que combina quatre tècniques òptiques innovadores: sistemes d'imatge multiespectral 3D, interferometria de retroalimentació i microscòpia confocal. El sistema portàtil desenvolupat inclou una càmera monocromàtica CCD, un objectiu i una font de llum formada per 32 díodes emissors de llum (LED) amb 8 bandes espectrals diferents que emeten des de 400 nm fins a 1000 nm. S'ha preparat un programa d'adquisició per controlar tots els components del sistema així com una versió més simple del mateix pels metges. Per tal d'assegurar el bon funcionament del sistema, es van analitzar els canvis temporals en l'emissió dels LEDs així com la seva uniformitat d'emissió, la resposta lineal de la càmera per cada longitud d'ona i la repetibilitat del sistema pel què fa a l'adquisició d'imatges. Per tal d'obtenir l'aprovació del Comitè Ètic i poder realitzar l'estudi clínic en els hospitals, es van dur a terme mesures d'irradiància i radiància d'acord amb la norma UNE-EN 62471. També es va implementar una interfície gràfica d'usuari (GUI) per al processament de les imatges espectrals i la seva corresponent anàlisi. Aquest algorisme permet calcular paràmetres espectrals i colorimètrics de la pell en termes de reflectància, absorbància i d'altres basats en el color. A més, inclús es va desenvolupar un algorisme de segmentació per extreure informació aïllada de cada lesió. Per a totes les imatges calculades en termes de qualsevol paràmetre, es van obtenir descriptors estadístics convencionals i també es van utilitzar propietats estadístiques dels histogrames com una primera aproximació d'extreure informació de textura de la lesió. Finalment, es van establir els criteris d'inclusió i un protocol de mesura. De totes les lesions analitzades, se'n van mesurar 620, de les quals 572 tenien un diagnòstic clínic o histopatològic; 502 es van poder segmentar adequadament. D'aquesta manera es van incloure 429 lesions cutànies a l'estudi: 290 nevus, 95 melanomes i 44 carcinomes de cèl·lules basals. Es va desenvolupar un algorisme de classificació per determinar si les lesions eren malignes (melanomes i carcinomes de cèl·lules basals) o no (nevus), dividint prèviament les dades en un grup d'entrenament i un altre de validació de la mateixa mida. Es va observar que 15 del 1309 paràmetres proporcionaven informació rellevant per a la classificació, obtenint una sensibilitat del 91,3% i una especificitat del 54,5%. Així doncs, es demostra que la incorporació d'informació de textura és molt útil per al diagnòstic del càncer de pell més enllà de la informació espectral i de color. Aquests mateixos passos es van seguir pel sistema 3D també inclòs en la plataforma multifotònica, tot i que en aquest cas el número de lesions de què es disposava era més limitat. En aquest cas, es van seleccionar 3 paràmetres i es va obtenir una sensibilitat del 55,6% i una especificitat del 83,7%. Finalment, amb la combinació d'ambdós sistemes la sensibilitat obtinguda va ser de100% i l'especificitat del 72,2%

Multimodal optical spectroscopy for application in the life sciences

Many optical modalities are being investigated, applied, and further developed for non-invasive analysis and sensing in the life sciences. Often, the combination of two or more modalities is required for in depth analysis because of the complexity of the study objects and questions in this field. The work presents multimodal sensing concepts for applications ranging from non-invasive quantification of biomolecules in the living organism to supporting medical diagnosis showing the combined capabilities of Raman spectroscopy, optical coherence tomography, and optoacoustic

Improved polarimetric analysis of human skin through stitching: advantages, limitations, and applications in dermatology

Polarimetry is a powerful tool for the analysis of the optical properties of materials and systems, such as human skin. However, in many polarimetric setups, the field of view is limited to a few square centimeters. In these cases, it is possible to resort to stitching techniques, which involve combining multiple Mueller matrix measurements obtained from different overlapping regions of the sample. In this paper, we propose a stitching technique for polarimetric data and discuss its advantages and limitations. We also describe the potential of image stitching for improving the accuracy and robustness of in vivo polarimetry in the presence of random patient movement. We conducted our research using a diverse set of samples which included porcine skin, human skin from arms and fingers, cold cuts of chicken and gelatine, alongside synthetically created sample data. Our results demonstrate the effectiveness of this technique for the application in dermatology. Each additional in vivo measurement enhances the field of view by approximately one third, thereby considerably augmenting the total observation area. We show that stitching enables for the polarimetric assessment of large skin patches which is useful for the diagnosis of inflammatory skin diseases