A novel visible and near-infrared hyperspectral imaging platform for automated breast-cancer detection

BACKGROUND

Breast cancer is a leading cause of cancer-related deaths among women worldwide. Early and accurate detection is crucial for improving patient outcomes. Our study utilizes Visible and Near-Infrared Hyperspectral Imaging (VIS-NIR HSI), a promising non-invasive technique, to detect cancerous regions in ex-vivo breast specimens based on their hyperspectral response.

METHODS

In this paper, we present a novel HSI platform integrated with fuzzy c-means clustering for automated breast cancer detection. We acquire hyperspectral data from breast tissue samples, and preprocess it to reduce noise and enhance hyperspectral features. Fuzzy c-means clustering is then applied to segment cancerous regions based on their spectral characteristics.

RESULTS

Our approach demonstrates promising results. We evaluated the quality of the clustering using metrics like Silhouette Index (SI), Davies-Bouldin Index (DBI), and Calinski-Harabasz Index (CHI). The clustering metrics results revealed an optimal number of 6 clusters for breast tissue classification, and the SI values ranged from 0.68 to 0.72, indicating well-separated clusters. Moreover, the CHI values showed that the clusters were well-defined, and the DBI values demonstrated low cluster dispersion. Additionally, the sensitivity, specificity, and accuracy of our system were evaluated on a dataset of breast tissue samples. We achieved an average sensitivity of 96.83%, specificity of 93.39%, and accuracy of 95.12%. These results indicate the effectiveness of our HSI-based approach in distinguishing cancerous and non-cancerous regions.

CONCLUSIONS

The paper introduces a robust hyperspectral imaging platform coupled with fuzzy c-means clustering for automated breast cancer detection. The clustering metrics results support the reliability of our approach in effectively segmenting breast tissue samples. In addition, the system shows high sensitivity and specificity, making it a valuable tool for early-stage breast cancer diagnosis. This innovative approach holds great potential for improving breast cancer screening and, thereby, enhancing our understanding of the disease and its detection patterns.

Automated hyperspectral imaging for non-invasive characterization of human eye vasculature: A potential tool for ocular vascular evaluation

The vascular supply to the human eye plays a vital role in maintaining ocular health, making its non-invasive evaluation essential for diagnosing and managing various ocular disorders. This paper presents a novel approach utilizing hyperspectral imaging (HSI) to non-invasively characterize human eye vasculature. The proposed system aims to specifically identify the blood atrium and veins of the human eye at 470 nm and 750 nm, respectively, using quantitative phase analysis and k-means clustering. The study involved capturing diffused reflection spectra and hyperspectral images of the human eye at different wavelengths to reveal distinctive vascular features. The results of ten volunteers demonstrate promising capabilities in automated differentiation of atrium and veins, as well as the potential for mapping varicose veins in the lower limb. This non-invasive and non-contact imaging technique shows great promise in facilitating accurate and detailed evaluation of ocular blood flow, providing valuable information for clinical diagnosis and treatment in ophthalmology and vascular medicine fields.

Multi-wavelength interference phase imaging for automatic breast cancer detection and delineation using diffuse reflection imaging

Millions of women globally are impacted by the major health problem of breast cancer (BC). Early detection of BC is critical for successful treatment and improved survival rates. In this study, we provide a progressive approach for BC detection using multi-wavelength interference (MWI) phase imaging based on diffuse reflection hyperspectral (HS) imaging. The proposed findings are based on the measurement of the interference pattern between the blue (446.6 nm) and red (632 nm) wavelengths. We consider implementing a comprehensive image processing and categorization method based on the use of Fast Fourier (FF) transform analysis pertaining to a change in the refractive index between tumor and normal tissue. We observed that cancer growth affects tissue organization dramatically, as seen by persistently increased refractive index variance in tumors compared normal areas. Both malignant and normal tissue had different depth data collected from it that was analyzed. To enhance the categorization of ex-vivo BC tissue, we developed and validated a training classifier algorithm specifically designed for categorizing HS cube data. Following the application of signal normalization with the FF transform algorithm, our methodology achieved a high level of performance with a specificity (Spec) of 94% and a sensitivity (Sen) of 90.9% for the 632 nm acquired image categorization, based on preliminary findings from breast specimens under investigation. Notably, we successfully leveraged unstained tissue samples to create 3D phase-resolved images that effectively highlight the distinctions in diffuse reflectance features between cancerous and healthy tissue. Preliminary data revealed that our imaging method might be able to assist specialists in safely excising malignant areas and assessing the tumor bed following resection automatically at different depths. This preliminary investigation might result in an effective "in-vivo" disease description utilizing optical technology using a typical RGB camera with wavelength-specific operation with our quantitative phase MWI imaging methodology.

Novel molecular laser-induced photoluminscence signature with hyperspectral imaging for instant and remote detection of trace explosive materials

Instant detection of explosive material is highly appreciated for counterterrorism activity and homeland security. Nitro group (high energy rich bond) is responsible for explosive characteristics. Nitro group includes intense competition between two highly electronegative atoms. Nitro group is frequently encountered in all explosive materials. This function group includes delocalized π bond; that could secure intense photoluminescence (fluorescence and phosphorescence) signature. In this study, the main classes of explosive materials including nitro-compounds (i.e. TNT), nitramines (i.e. RDX), and nitric esters (i.e. PETN) were stimulated with green laser source of 532 nm and 5 mW power. The photoluminescence signature of each tested material was captured via hyperspectral camera. The tested explosives demonstrated characteristic fluorescence signature at 571, 587, and 613 nm for RDX, PETN, and TNT respectively. Furthermore, TNT demonstrated characteristic phosphorescence signature at 975 nm. The customized laser induced photoluminescence technique offered facile detection of trace explosive material via clustering approach based on K-m clustering (k = 8); this technique was able to detect RDX, PETN and TNT traces on the finger nail via processed hyperspectral images at 581 nm, 797 nm and 953 nm, respectively. This study shaded the light on novel customized photoluminescence technique for facile detection and identification of trace explosive materials.

Development of a custom optical imaging system for non-invasive monitoring and delineation of lower limb varicose veins using hyperspectral imaging and quantitative phase analysis

BACKGROUND

Varicose veins (VV) are a prevalent chronic venous disorder, particularly affecting women of childbearing age. This condition is associated with significant complications, including pain, discomfort, leg cramps, ulceration, reduced quality of life, absenteeism, and even mortality. This study aims to develop a custom non-invasive, non-contact optical imaging system combined with magnitude and phase image calculation to monitor and visualize varicose veins and their tributaries using hyperspectral imaging and quantitative phase analysis with a k-means clustering algorithm.

RESULTS

Ten volunteers participated in the optical imaging system study. They were exposed to a polychromatic light source spanning the wavelength range of 400 nm-950 nm. The diffuse reflection spectra for varicose veins exhibited a peak at 530 nm, while leg veins showed a peak at 780 nm. Hyperspectral images obtained at these specific wavelengths were normalized in order to homogenize the spectral signatures of each pixel (converting the hyperspectral image to 8 bit RGB image) and filtered using a moving average filter. Subsequently, the varicose veins and leg veins were delineated and detected using quantitative phase analysis and a k-means clustering algorithm.

CONCLUSION

In conclusion, the custom optical imaging system, utilizing hyperspectral imaging and the associated clustering algorithm, provides detailed information regarding the spatial distribution of varicose veins. This information can assist vascular physicians in facilitating easier diagnosis and treatment planning.

Delineation and detection of breast cancer using novel label-free fluorescence

BACKGROUND

Accurate diagnosis of breast cancer (BC) plays a crucial role in clinical pathology analysis and ensuring precise surgical margins to prevent recurrence.

METHODS

Laser-induced fluorescence (LIF) technology offers high sensitivity to tissue biochemistry, making it a potential tool for noninvasive BC identification. In this study, we utilized hyperspectral (HS) imaging data of stimulated BC specimens to detect malignancies based on altered fluorescence characteristics compared to normal tissue. Initially, we employed a HS camera and broadband spectrum light to assess the absorbance of BC samples. Notably, significant absorbance differences were observed in the 440-460 nm wavelength range. Subsequently, we developed a specialized LIF system for BC detection, utilizing a low-power blue laser source at 450 nm wavelength for ten BC samples.

RESULTS

Our findings revealed that the fluorescence distribution of breast specimens, which carries molecular-scale structural information, serves as an effective marker for identifying breast tumors. Specifically, the emission at 561 nm exhibited the greatest variation in fluorescence signal intensity for both tumor and normal tissue, serving as an optical predictive biomarker. To enhance BC identification, we propose an advanced image classification technique that combines image segmentation using contour mapping and K-means clustering (K-mc, K = 8) for HS emission image data analysis.

CONCLUSIONS

This exploratory work presents a potential avenue for improving "in-vivo" disease characterization using optical technology, specifically our LIF technique combined with the advanced K-mc approach, facilitating early tumor diagnosis in BC.

Instant identification of dental white spot using K-means algorithm via laser-induced fluorescence and associated hyperspectral imaging

Dental caries (DC) is a chronic illness that affects 2 billion individuals worldwide, with 520 million of those suffering from it in their primary teeth. It is apparent that early DC detection and subsequent minimally invasive therapy are crucial clinical requirements. The first reversible clinical indication of demineralization is dental white spot (DWS) lesions. However, diagnosing DWS poses extreme challenges for practitioners. In this investigation, a customized laser-induced fluorescence system with a hyperspectral imaging (HI) camera and a non-ionization laser light supply was created for DWS localization and early DC detection. A UV laser diode source with a wavelength of 395 nm was used for light stimulation for the 10 test samples of teeth. The emitted signature of the main tooth components, including dentin, DWS, enamel, and DC, was recorded. An attempt was made to increase the system's sensitivity to the fluorescent signal by applying a logarithmic scale to the spectral signature. Moreover, further discrimination may be achieved by signal strength. We identified that the fluorescent signal's peak intensity at 771 nm works best for discriminating DWS from normal areas, or DC. For characterizing dentin, the re-emitted frequency at 500 nm has the maximum intensity. Next, we presented our imaging grouping strategy that combines visual enhancement through a moving average, MA, filtering and segmenting an image using K-means clustering (K-mc) (K = 8) for instant and precise DWS grouping for the constructed HI images at (500 nm and 771 nm). Despite the tiny structure and its DWS white appearance, our approach could successfully demarcate the DWS on the tested teeth. Dental examiners might benefit from our simple, non-invasive, non-ionizing optical diagnosis approach to help them make their first assessments and experience accurate and exact delineation of the DWS to obtain immediate and higher rates of early-stage DC detection.

Malignant versus normal breast tissue: Optical differentiation exploiting hyperspectral imaging system

Breast malignancy is a critical problem that severely affects women’s health globally with a high-frequency rate, necessitating fast, effective, and early diagnostic methods. The present study aims to measure the breast tissue’s optical properties by capturing the spectral signatures from malignant and normal breast tissue for therapeutic and diagnostic applications. The optical imaging system incorporates a hyperspectral (HS) camera to capture the spectral signatures for both the malignant and normal breast tissues within 400 ~ 1000 nm. The system was subdivided into two exploratory (reflection/transmission) to measure the tissue’s diffuse reflectance (Rd) and light transmission (Tr), respectively. The study involved 30 breast tissue (normal/tumor) samples from 30 females in the age range of 46 ~ 72 years, who were optically inspected in the visible and near-infrared (VIS-NIR) spectra. Then, the inverse adding doubling (IAD) method for breast tissue characterization and descriptive analysis (T-test) was exploited to verify the significant difference between the various types of breast tissues and select the optimum wavelength. Finally, comparing the study outcome with the histopathological examination to evaluate the system’s effectiveness by calculation (sensitivity, specificity, and accuracy). The average outcome values demonstrated that the optimal spectral bands distinguishing between the normal and the tumor tissues regarding the reflectance approach were 600 ~ 680 nm and 750 ~ 960 nm at the VIS and NIR spectrum, respectively. Then, for the transmission technique, the optimal spectral bands were 560 ~ 590 nm and 760 ~ 810 nm at the VIS and NIR spectra, respectively. Later, the T-test and the IAD verified that the highest Rd values for discrimination were 600 ~ 640 nm and 800 ~ 840 nm at the VIS and NIR spectra, respectively. On the other side, the highest Tr values were 600 ~ 640 nm and 760 ~ 800 nm at the VIS and NIR spectra, respectively. The investigation’s average reading accuracy, sensitivity, and specificity were 85%, 81.88%, and 88.8%, respectively. The experimental trials revealed that the system could identify the optimal wavelength for therapeutic and diagnostic applications through the light interaction behavior of the breast tissue’s optical properties.

Emerging Technology for Intraoperative Margin and Assisting in Post-Surgery tissue diagnostic for Future Breast-Conserving

INTRODUCTION

Tissue-preserving surgery is utilized progressively in cancer therapy, where a clear surgical margin is critical to avoid cancer recurrence, specifically in breast cancer (BC) surgery. The Intraoperative pathologic approaches that rely on tissue segmenting and staining have been recognized as the ground truth for BC diagnosis. Nevertheless, these methods are constrained by its complication and timewasting for tissue preparation.

OBJECTIVE

We present a non-invasive optical imaging system incorporating a hyperspectral (HS) camera to discriminate between cancerous and non-cancerous tissues in ex-vivo breast specimens, which could be an intraoperative diagnostic technique to aid surgeons during surgery and later a valuable tool to assist pathologists.

METHODS

We have established a hyperspectral Imaging (HSI) system comprising a push-broom HS camera at wavelength 380∼1050 nm with source light 390∼980 nm. We have measured the investigated samples' diffuse reflectance (R_d), fixed on slides from 30 distinct patients incorporating mutually normal and ductal carcinoma tissue. The samples were divided into two groups, stained tissues during the surgery (control group) and unstained samples (test group), both captured with the HSI system in the visible and near-infrared (VIS-NIR) range. Then, to address the problem of the spectral nonuniformity of the illumination device and the influence of the dark current, the radiance data were normalized to yield the radiance of the specimen and neutralize the intensity effect to focus on the spectral reflectance shift for each tissue. The selection of the threshold window from the measured R_d is carried out by exploiting the statistical analysis by calculating each region's mean and standard deviation. Afterward, we selected the optimum spectral images from the HS data cube to apply a custom K-means algorithm and contour delineation to identify the regular districts from the BC regions.

RESULTS

We noticed that the measured spectral R_d for the malignant tissues of the investigated case studies versus the reference source light varies regarding the cancer stage, as sometimes the R_d is higher for the tumor or vice versa for the normal tissue. Later, from the analysis of the whole samples, we found that the most appropriate wavelength for the BC tissues was 447 nm, which was highly reflected versus the normal tissue. However, the most convenient one for the normal tissue was at 545 nm with high reflection versus the BC tissue. Finally, we implement a moving average filter for noise reduction and a custom K-means clustering algorithm on the selected two spectral images (447, 551 nm) to identify the various regions and effectively-identified spectral tissue variations with a sensitivity of 98.95%, and specificity of 98.44%. A pathologist later confirmed these outcomes as the ground truth for the tissue sample investigations.

CONCLUSIONS

The proposed system could help the surgeon and the pathologist identify the cancerous tissue margins from the non-cancerous tissue with a non-invasive, rapid, and minimum time method achieving high sensitivity up to 98.95%.

Quantitative phase analysis and hyperspectral imaging for the automatic identification of veins and blood perfusion maps

INTRODUCTION

Medical workers commonly physically identify subcutaneous veins to locate a suitable vesselto implant a catheter for drug administration or blood sample. The general rule of thumb is to locate a big, clean vein that will allow the medication to readily pass within the intended blood vessel. Peripheral problematic venous access happens when a patient's veins are difficult to palpate because of factors like dark skin tone, edema or excess tissue. The ability to see how the vasculature changes to support the therapeutic methods without damaging the surrounding tissue is another challenge.

MATERIALS AND METHODS

Hyperspectral imaging (HI) is a developing technique with several potential uses in medicine. Using its spectroscopic data, veins and arterioles could be noninvasively detected and discriminated. It is frequently important to use quantitative phase analysis for vein localization. To assess hyperspectral image data for the detection of both veins and peripheral arteries, we suggest using an advanced image processing and classification algorithm based on the phase information related to the index of refraction change and associated scattering. We show that this need may be satisfied using quantitative phase imaging of forearm skin tissue at different depths.

RESULTS

To demonstrate the variations in the diffuse reflectance characteristics between skin surface and veins, phase resolved pictures were successfully produced for twelve volunteers using our imaging methodology. We found that the skin surface details are completely apparent at the unique wavelength of 441 nm. The 500-nm wavelength was the most efficient for grouping peripheral arteries and illuminating the blood perfusion maps. Using our HI experimental setup and our phase imaging procedure on the 600 nm and 650 nm visible spectral pictures, we were able to properly describe the vein map. This spectral area may be utilized as a vein locator marker which could approximately reach till 3 mm depth under skin surface.

CONCLUSIONS

Initial findings suggested that our imaging technique would be able to assist medical examiners in safely assessing the veins and arteriole's locations automatically without exposing the skin to infrared radiation. Meanwhile, our pilot research in this work to determine the best spectral wavelengths for localizing veins and mapping blood perfusion using our phase analysis imaging strategy with the HI camera. By substituting the HI camera with a custom conventional RGB camera that only functions at specific wavelengths during the discovering of blood perfusion locations or prior to intravenous catheterization, a distinctive and efficient system for precise identification may be developed to serve in the field of the vascular therapeutic methods.

Non-invasive caries detection and delineation via novel laser-induced fluorescence with hyperspectral imaging

Carious is a global chronic disease; 2 billion people and 520 million children suffer from permanent and primary teeth caries respectively. Early caries detection via precise, non-invasive, non-ionizing radiation is highly appreciated. Carious deteriorate the chemical structure of sound tooth tissues, with variation in its optical properties. In this study, customized laser-induced fluorescence system consists of non-ionizing laser light source and hyperspectral camera was developed for early caries detection. Tested tooth sample was illuminated with laser source of 385 nm and 5 mW power. The emitted spectrum signature for main tooth elements including enamel, dentin, stain, and caries were captured. Logarithmic scale of spectrum signature was applied in an attempt to enhance system sensitivity to fluorescent signal. Fluorescence signature at 500 nm secured the maximum fluorescence intensity difference for different tooth elements. Consequently 2D hyperspectral image at 500 nm was constructed. Enhanced 2D image was accomplished via nonlinear filter to enhance contrast. Segmentation via K mean clustering was adopted for precise caries delineation. This narrative, facile, non-invasive, non-ionizing technique experienced precise and accurate delineation of different caries stages (normal, moderate, and severe).

Oxygen saturation measurements using novel diffused reflectance with hyperspectral imaging: Towards facile COVID-19 diagnosis

Oxygen saturation level plays a vital role in screening, diagnosis, and therapeutic assessment of disease's assortment. There is an urgent need to design and implement early detection devices and applications for the COVID-19 pandemic; this study reports on the development of customized, highly sensitive, non-invasive, non-contact diffused reflectance system coupled with hyperspectral imaging for mapping subcutaneous blood circulation depending on its oxygen saturation level. The forearm of 15 healthy adult male volunteers with age range of (20-38 years) were illuminated via a polychromatic light source of a spectrum range 400-980 nm. Each patient had been scanned five times to calculate the mean spectroscopic reflectance images using hyperspectral camera. The customized signal processing algorithm includes normalization and moving average filter for noise removal. Afterward, employing K-means clustering for image segmentation to assess the accuracy of blood oxygen saturation (SpO₂) levels. The reliability of the developed diffused reflectance system was verified with the ground truth technique, a standard pulse oximeter. Non-invasive, non-contact diffused reflectance spectrum demonstrated maximum signal variation at 610 nm according to SpO₂ level. Statistical analysis (mean, standard deviation) of diffused reflectance hyperspectral images at 610 nm offered precise calibrated measurements to the standard pulse oximeter. Diffused reflectance associated with hyperspectral imaging is a prospective technique to assist with phlebotomy and vascular approach. Additionally, it could permit future surgical or pharmacological intercessions that titrate or limit ischemic injury continuously. Furthermore, this technique could offer a fast reliable indication of SpO₂ levels for COVID-19 diagnosis.

Total RNA nonlinear polarization: towards facile early diagnosis of breast cancer

Different cancers are caused by accumulation of numerous genetic and epigenetic changes. Recently, nonlinear polarization has been considered as a marvelous tool for several medical applications. The capability of nonlinear polarization, to monitor any changes in RNA's spectral signature due to breast cancer (BC) was evaluated. Blood samples, from healthy controls and BC patients, were collected for whole blood preparation for genomic total RNA purification. Total RNA samples were stimulated with a light-emitting diode (LED) source of 565 nm; the resonance frequency of investigated RNA samples was captured and processed via hyperspectral imaging. Resonance frequency signatures were processed using fast Fourier transform in an attempt to differentiate between RNA (control) and RNA (BC) via frequency response. RNA (BC) demonstrated a characteristic signal at 0.02 GHz, as well as a phase shift at 0.031, and 0.070 GHZ from RNA (control). These features could offer early BC diagnosis. This is the first time to describe an optical methodology based on nonlinear polarization as a facile principle to distinguish and identify RNA alterations in BC by their characteristic fingerprint spectral signature.

Nonlinear polarization has been considered as a marvelous tool for several medical applications, and the capability to monitor any changes in RNA's spectral signature due to breast cancer was evaluated by hyperspectral camera.

Integration of transcriptomes analysis with spectral signature of total RNA for generation of affordable remote sensing of Hepatocellular carcinoma in serum clinical specimens

Hepatocellular carcinoma (HCC) is a major global health problem with about 841,000 new cases and 782,000 deaths annually, due to lacking early biomarker/s, and centralized diagnosis. Transcriptomes research despite its infancy has proved excellence in its implementation in identifying a coherent specific cancer RNAs differential expression. However, results are sometimes overlapped by other cancer types which negatively affecting specificity, plus the high cost of the equipment used. Hyperspectral imaging (HSI) is an advanced tool with unique, spectroscopic features, is an emerging tool that has widely been used in cancer detection. Herein, a pilot study has been performed for HCC diagnosis, by exploiting HIS properties and the analysis of the transcriptome for the development of non-invasive remote HCC sensing. HSI data cube images of the sera extracted total RNA have been analyzed in HCC, normal subject, liver benign tumor, and chronic HCV with cirrhotic/non-cirrhotic liver groups. Data analyses have revealed a specific spectral signature for all groups and can be easily discriminated; at the computed optimum wavelength. Moreover, we have developed a simple setup based on a commercial laser pointer for sample illumination and a Smartphone CCD camera, with HSI consistent data output. We hypothesized that RNA differential expression and its spatial organization/folding are the key players in the obtained spectral signatures. To the best of our knowledge, we are the first to use HSI for sensing cancer based on total RNA in serum, using a Smartphone CCD camera/laser pointer. The proposed biosensor is simple, rapid (2 min), and affordable with specificity and sensitivity of more than 98% and high accuracy.

3D spectral fluorescence signature of cerium(III)-melamine coordination polymer: A novel sensing material for explosive detection

Hidden or buried explosives are the most common scenario by terrorist attacks; therefore explosive vapour detection is a vital demand. Explosives are electron deficient materials; the vicinity of explosives to fluorescent material can encounter electron migration. This study reports on facile synthesis of cerium (III)-melamine coordination polymer (CeM-CP) with exclusive optical properties. CeM-CP demonstrated novel spectral fluorescence properties over visible and infrared bands when stimulated with UVA LED source at 385 nm of 100 mW power. Stimulated CeM-CP demonstrated unique spectral fluorescence signal at 400, 700, and 785 nm. These fluorescent signals were correlated to cerium coordination with four nitrogen atoms; vacant orbital will be available for electron excitation migration. Spectral fluorescent signals were quenched as CeM-CP was subjected to TNT vapours. Hyperspectral imaging offered 3D plot of fluorescence signature. The main outcome is that complete fluorescence signal attenuation was achieved at 785 nm. CeM-CP could act as as a novel sensing element for explosive vapour detection.

Custom optical imaging system for ex-vivo breast cancer detection based on spectral signature

BACKGROUND AND PURPOSE

Breast cancer is a popular well-known tumor in women globally and the subsequent driving reason for malignancy death. The purpose of the present study is to develop Low cost, commercial, and affordable system that discriminates malignant from normal breast tissues by exploiting the unique properties of Hyperspectral (HS) Imaging.

MATERIALS AND METHODS

The difference in the optical properties of the investigated breast tissues gives various reactions to light transmission, absorption, and especially the reflection over the spectral range. A custom optical imaging system (COIS) was designed to assess variable responses to monochromatic LEDs (415, 565, 660 nm) to highlight the differences in the reflectance properties of malignant/normal tissue. Statistical analysis was computed for determining the ideal wavelength to differentiate between normal and malignant regions. The experiment was repeated using the same LEDs, and low-cost CCD camera to examine the capability of such a system to discriminate between normal and malignant tissue.

RESULTS

Spectral images obtained by Hyperspectral camera, have been analyzed to reveal the difference of reflectance malignant and normal breast tissue. Superficial spectral reflection image with blue LED (415 nm) showed high variance (10.11). However, a more-depth reflection image with red LED (660 nm) showed low variance (4.44). So the optimum contrast image was produced by combining the three spectral information images from blue, green, and red LED. The COIS using a commercial CCD camera was in agreement with the HS camera.

CONCLUSIONS

The novel COIS of the commercial Low-cost CCD Camera is reliable and can be used with endoscopy technique as an assistant tool for surgical doctor to make decision and assess the resection edges in real time during surgery.

Laser induced fluorescence with 2-D Hilbert transform edge detection algorithm and 3D fluorescence images for white spot early recognition

OBJECTIVE

There is a must for non-invasive caries detection method to supplement traditional visual assessment by the clinician before lesion progression reaches a stage requiring invasive therapy.

MATERIAL AND METHODS

In this paper, the nature of tissue response to light interaction has been used for early diagnosis, using laser induced fluorescence spectroscopy. Human tooth sample was illuminated with He-Ne laser sources (633 nm) with energy 5 mW. The reflected and emitted spectra of investigated samples were collected using hyperspectral camera to develop multispectral images. The variation of reflected and emitted energy as function in wavelength was employed to generate characteristic spectrum of each tooth tissue. Human teeth caries lesion releases their excess energy by emitting fluorescence light producing chemical footprint signature for each tooth elements and caries state.

RESULTS

This non-invasive, non-contact, and non-ionizing hyperspectral imaging system was employed to diagnose and classify different caries types and stages. Reconstructed 3D fluorescence images offered discrimination between enamel and dentin caries at 633 nm illumination spectral line; white spot lesion was clearly detected and recognized at far visible and infrared wavelength ranges.

CONCLUSION

This study reports on customized optical imaging system that can offer high sensitivity, high resolution. Optimum stimulating wavelength for early caries detection was reported to be 633 nm. This novel approach can offer a full map of caries degree status.

Hyperspectral imaging for diagnosis and detection of ex-vivo breast cancer

BACKGROUND AND PURPOSE

Breast cancer is one of the most widely recognized tumors. .Diagnosis made in the early stage of disease may imporve outcomes. The discovery of malignant growth utilizing noninvasive light intrusive methods in lieu of conventional excisional biopsy may assist in achieving this goal.

MATERIALS AND METHODS

The change of the optical properties of ex-vivo breast tissues provides different responses to light transmission, absorption, and particularly the reflection over the spectrum range. We offer the use of Hyperspectral imaging (HSI) with advanced image processing and pattern recognition in order to analyze HSI data for breast cancer detection. The spectral signatures were mined and evaluated in both malignant and normal tissue. K-mean clustering was designed for classifying hyperspectral data in order to evaluate and detection of cancer tissue. This method was used to detect ex-vivo breast cancer. Spatial spectral images were created to high spot the differences in the reflectance properties of malignant versus normal tissue.

RESULTS

Trials showed that the superficial spectral reflection images within 500 nm wavelength showed high variance (214.65) between cancerous and normal breast tissues. On the other hand, image within 620 nm wavelength showed low variance (0.0020).However, the superimposed of spectral region 420-620 nm was proposed as the optimum bandwidth. Finally, the proposed HS imaging system was capable to discriminate the tumor region from normal tissue of the ex-vivo breast sample with sensitivity and a specificity of 95 % and 96 %.

CONCLUSIONS

High sensitivity and specificity were achieved, which proposes potential for HSI as an edge evaluation method to enhance the surgical outcome compared to the presently available techniques in the clinics.

Surface modified colloidal silica nanoparticles: Novel aspect for complete identification of explosive materials

Terrorism by means of explosives has become a crucial threat. Nanoparticles with distinctive properties can offer novel aspects for instant detection of explosive materials. Common explosives are organic compounds that contain nitro group (NO₂) along with carbon and hydrogen elements. This study demonstrates complete identification of nitramine explosives (RDX & HMX) using colloidal silica nanoparticles. Sustainable fabrication of colloidal silica was conducted via hydrothermal processing technique. Explosive identification involves a digestion of the tested material using strong acid. The digestion process results in the development of nitro group and corresponding formaldehyde segment. The identification of the nitro group was performed using colloidal silica nanoparticles functionalized with secondary amine to develop a characteristic dark blue colour. Simultaneous identification of formaldehyde segment was performed using colloidal silica functionalized with aromatic phenol to develop a red colour. This robust explosive detection technology can find wide applications on site where instant identification to assess potential threat is a crucial demand. Thanks to hydrothermal processing, sustainable fabrication and surface modification of colloidal silica particles can be obtained.

Real time recognition of explosophorous group and explosive material using laser induced photoacoustic spectroscopy associated with novel algorithm for time and frequency domain analysis

Energy-rich bonds such as nitrates (NO₃^-) and percholorates (ClO₄^-) have an explosive nature; they are frequently encountered in high energy materials. These bonds encompass two highly electronegative atoms competing for electrons. Common explosive materials including urea nitrate, ammonium nitrate, and ammonium percholorates were subjected to photoacoustic spectroscopy. The captured signal was processed using novel digital algorithm designed for time and frequency domain analysis. Frequency domain analysis offered not only characteristic frequencies for NO₃^- and ClO₄^- groups; but also characteristic fingerprint spectra (based on thermal, acoustical, and optical properties) for different materials. The main outcome of this study is that phase-shift domain analysis offered an outstanding signature for each explosive material, with novel discrimination between explosive and similar non-explosive material. Photoacoustic spectroscopy offered different characteristic signatures that can be employed for real time detection with stand-off capabilities. There is no two materials could have the same optical, thermal, and acoustical properties.

Design and implementation of novel hyperspectral imaging for dental carious early detection using laser induced fluorescence

Early detection of carious is vital for demineralization reversal, offering less pain, as well as precise carious removal. In this study, the difference in optical properties of normal tissue and human carious lesion has been used for early diagnosis, using laser induced fluorescence spectroscopy. The optical system consists of light source in visible band and hyperspectral camera, associated with designed digital image processing algorithm. The human tooth sample was illuminated with visible band sources at 488, and 514 nm with energy of 5 m watt. The reflected and emitted light from the tested sample was captured using hyperspectral camera in an attempt to generate multispectral images (cubic image). The variation of reflected and emitted energy as function of wavelength was employed to generate characteristic spectrum of each tooth tissue. Human teeth carious tissue lesion releases its excess energy by emitting fluorescence light producing chemical footprint signature; this signature is dependent on the elemental composition of tooth elements and carious state. This non-invasive, non-contact and non-ionizing imaging system with associated novel pattern recognition algorithm was employed to diagnose and classify different carious types and stages. It was reported that the perceived fluorescence emission is function of the illuminating wavelength. While enamel and dentin carious were distinguished and characterized at 514 nm illuminating wavelength; white spot lesion were contoured and recognized at 488 nm. Therefore, full recognition could be achieved through generated cubic image after sample irradiation at 488 nm and 514 nm. In conclusion, this study reports on a customized optical image system that can offer high sensitivity, high resolution, and early carious detection with optimum performance at 514 nm and 488 nm.

High-performance near-infrared imaging for breast cancer detection

We present a method for the noninvasive determination of the size, position, and optical properties of tumors in the human breast. The tumor is first detected by photothermal imaging. It is then sized, located, and optically characterized using designed digital image processing and edge-detection pattern recognition. The method assumes that the tumor is spherical and inhomogeneous and embedded in an otherwise homogeneous tissue. Heat energy is deposited in the tissue by absorption of near-infrared (NIR) Nd:YAG laser radiation, and its subsequent conversion to heat via vibrational relaxation causes a rise in temperature of the tissue. The tumor absorbs and scatters NIR light more strongly than the surrounding healthy tissue. Heat will diffuse through the tissue, causing a rise in temperature of the surrounding tissue. Differentiation between normal and cancerous tissues is determined using IR thermal imaging. Results are presented on a 55-year-old patient with a papillary breast cancer. We found that these results provide the clinician with more detailed information about breast lesions detected by photothermal imaging and thereby enhance its potential for specificity.