Medical Imaging

The demand for interdisciplinary research is increasing in the new millennium to help us understand complex problems and find solutions by integrating the knowledge from different disciplines. The present review is an excellent example of this and shows how unique combination of physics, chemistry, and biological techniques can be used for the evaluation of Indian medicinal herbs used for treating diabetes mellitus. Laser-induced breakdown spectroscopy (LIBS) is a sensitive optical technique that is widely used for its simplicity and versatility. This review presents the most recent application of LIBS for detection of glycemic elements in medicinal plants. The characteristics of matrices, object analysis, use of laser system, and analytical performances with respect to Indian herbs are discussed.

Purpose: Many interventional procedures require the precise placement of needles or therapy applicators (tools) to correctly achieve planned targets for optimal diagnosis or treatment of cancer, typically leveraging the temporal resolution of ultrasound (US) to provide real-time feedback. Identifying tools in two-dimensional (2D) images can often be time-consuming with the precise position difficult to distinguish. We have developed and implemented a deep learning method to segment tools in 2D US images in near real-time for multiple anatomical sites, despite the widely varying appearances across interventional applications. Methods: A U-Net architecture with a Dice similarity coefficient (DSC) loss function was used to perform segmentation on input images resized to 256⨯256 pixels. The U-Net was modified by adding 50 % dropouts and the use of transpose convolutions in the decoder section of the network. The proposed approach was trained with 917 images and manual segmentations from prostate/gynecologic brachytherapy, liver ablation, and kidney biopsy/ablation procedures, as well as phantom experiments. Real-time data augmentation was applied to improve generalizability and doubled the dataset for each epoch. Post-processing to identify the tool tip and trajectory was performed using two different approaches, comparing the largest island with a linear fit to random sample consensus (RANSAC) fitting. Comparing predictions from 315 unseen test images to manual segmentations, the overall median [first quartile, third quartile] tip error, angular error, and DSC were 3.5 [1.3, 13.5] mm, 0.8 [0.3, 1.7]°, and 73.3 [56.2, 82.3] %, respectively, following RANSAC post-processing. The predictions with the lowest median tip and angular errors were observed in the gynecologic images (median tip error: 0.3 mm; median angular error: 0.4°) with the highest errors in the kidney images (median tip error: 10.1 mm; median angular error: 2.9°). The performance on the kidney images was likely due to a reduction in acoustic signal associated with oblique insertions relative to the US probe and the increased number of anatomical interfaces with similar echogenicity. Unprocessed segmentations were performed with a mean time of approximately 50 ms per image. We have demonstrated that our proposed approach can accurately segment tools in 2D US images from multiple anatomical locations and a variety of clinical interventional procedures in This article is protected by copyright. All rights reserved near real-time, providing the potential to improve image guidance during a broad range of diagnostic and therapeutic cancer interventions.

Relief holograms are obtained on Agfa 8E56HD holographic emulsions by a Russian chemical-processing technique that is developed for their PE-2 holographic emulsion. We have shown that the threedimensional surface profiles can easily be visualized by applying atomic force microscopy to measurement of the relief depth and relief spacing on holographic emulsions. The relief depth and thus diffraction efficiency decreases with increasing exposure time.

We present a software package which uniquely integrates several facets of image-guided medicine into a single portable, extendable environment. It provides capabilities for automatic registration, semiautomatic segmentation, 3D surface model generation, 3D visualization, and quantitative analysis of various medical scans. We describe its system architecture, wide range of applications, and novel integration with an interventional Magnetic Resonance (MR) scanner to augment intraoperative imaging with pre-operative data. Analysis previously reserved for pre-operative data can now be applied to exploring the anatomical changes as the surgery progresses. Surgical instruments are tracked and used to drive the location of reformatted slices. Real-time scans are visualized as slices in the same 3D view along with the pre-operative slices and surface models. The system has been applied in over 20 neurosurgical cases at Brigham and Women's Hospital, and continues to be routinely used for 1-3 cases per week. 1 1 Ron Kikinis and Ferenc Jolesz received partial support from NIH grants P41 RR13218-01, P01 CA67165-03, and R01 RR11747-01A. Eric Grimson received partial support from NSF grant IIS-9610249.

This investigation presents a groundbreaking deep learning approach for the
early recognition and differentiation of Alzheimer's Disease (AD), a
widespread neurological disorder, employing non-invasive cerebral imaging
techniques. By combining state-of-the-art deep learning algorithms with
feature fusion methodologies, the research seeks to boost the accuracy and
consistency of AD diagnosis, potentially facilitating earlier intervention and
individualized treatment approaches. The framework utilizes multiple imaging
modalities, such as Magnetic Resonance Imaging (MRI) and Positron
Emission Tomography (PET), to extract complementary features that reflect
both structural and functional brain alterations associated with AD. An
advanced feature fusion strategy is implemented to integrate these
heterogeneous data sources into a unified representation, allowing the deep
learning model to discern more intricate and distinctive patterns of
neurodegeneration. The deep neural network, trained on an extensive,
clinically diverse dataset, is engineered to identify subtle AD biomarkers,
even in preclinical phases, offering a robust tool for healthcare professionals.
By concentrating on non-invasive brain imaging techniques, the proposed
methodology presents a promising alternative to traditional diagnostic
procedures, which often involve invasive or time-consuming examinations.
The integration of clinical expertise and sophisticated machine learning in
this framework provides a powerful resource for neurological specialists,
enhancing diagnostic precision and supporting more informed therapeutic
decisions. Ultimately, this study showcases the potential of deep learning and
feature fusion techniques to revolutionize the clinical approach to AD
diagnosis, marking a significant advancement toward more efficient and
accessible healthcare solutions.

Laser interference fringe tomography (LIFT) is within the class of optical imaging devices designed for in vivo and ex vivo medical imaging applications. LIFT is a very simple and cost-effective three-dimensional imaging device with performance rivaling some of the leading three-dimensional imaging devices used for histology. Like optical coherence tomography (OCT), it measures the reflectivity as a function of depth within a sample and is capable of producing three-dimensional images from optically scattering media. LIFT has the potential capability to produce high spectral resolution, full-color images. The optical design of LIFT along with the planned iterations for improvements and miniaturization are presented and discussed in addition to the theoretical concepts and preliminary imaging results of the device.

This article describes a method called Lorentz Force Electrical Impedance Tomography. The electrical conductivity of biological tissues can be measured through their sonication in a magnetic field : the vibration of the tissues inside the field induces an electrical current by Lorentz force. This current, detected by electrodes placed around the sample, is proportional to the ultrasonic pressure, to the strength of the magnetic field and to the electrical conductivity gradient along the acoustic axis. By focusing at different places inside the sample, a map of the electrical conductivity gradient can be established. In this study experiments were conducted on a gelatin phantom and on a beef sample, successively placed in a 300 mT magnetic field and sonicated with an ultrasonic transducer focused at 21 cm emitting 500 kHz bursts. Although all interfaces are not visible, in this exploratory study a good correlation is observed between the electrical conductivity image and the ultrasonic image. This method offers an alternative to detecting pathologies invisible to standard ultrasonography.

Two long-period gratings (LPGs) fabricated in series in an optical fiber form a Mach-Zehnder interferometer, producing a sinusoidal channelled spectrum within the characteristic LPG attenuation bands, which has the appearance of an interference fringe pattern. The phase of the fringes is sensitive to changes in the surrounding environmental parameters, such as refractive index. Fabrication of a number of identical cascaded LPG pairs with different separations produces independent fringe patterns of different frequencies within the attenuation bands. The application of basic Fourier techniques to analyze the transmission spectrum allows the phase of each fringe pattern to be determined independently, facilitating the differentiation of external effects acting on each interferometer.

As traditional visual-examination-based methods provide neither reliable nor consistent wound assessment, several computer-based approaches for quantitative wound image analysis have been proposed in recent years. However, these methods require either some level of human interaction for proper image processing or that images be captured under controlled conditions. However, to become a practical tool of diabetic patients for wound management, the wound image algorithm needs to be able to correctly locate and detect the wound boundary of images acquired under less-constrained conditions, where the illumination and camera angle can vary within reasonable bounds. We present a wound boundary determination method that is robust to lighting and camera orientation perturbations by applying the associative hierarchical random field (AHRF) framework, which is an improved conditional random field (CRF) model originally applied to natural image multiscale analysis. To validate the robustness of the AHRF framework for wound boundary recognition tasks, we have tested the method on two image datasets: (1) foot and leg ulcer images (for the patients we have tracked for 2 years) that were captured under one of the two conditions, such that 70% of the entire dataset are captured with image capture box to ensure consistent lighting and range and the remaining 30% of the images are captured by a handheld camera under varied conditions of lighting, incident angle, and range and (2) moulage wound images that were captured under similarly varied conditions. Compared to other CRF-based machine learning strategies, our new method provides a determination accuracy with the best global performance rates (specificity: >95% and sensitivity: >77%.

This paper presents a system to support medical diagnosis and detection of abnormal lesions by processing endoscopic images. Endoscopic images possess rich information expressed by texture. Texture information can be efficiently extracted from medium scales of the wavelet transform. The set of features proposed in this paper to encode textural information is named color wavelet covariance (CWC). CWC coefficients are based on the covariances of second order textural measures, an optimum subset of them is proposed. The proposed approach is supported by a classifier based on multilayer perceptron network for the characterization of the image regions along the video frames. The whole methodology has been applied on real data containing 6 full endoscopic exams and reached 87% specificity and 97.4% sensitivity.

Transparent optical networks are the enabling infrastructure for converged multi-granular networks in the Future Internet. The cross-layer planning of these networks considers physical impairments in the network layer design. This is complicated by the diversity of modulation formats, transmission rates, amplification and compensation equipments, or deployed fiber links. Thereby, the concept of Quality of Transmission (QoT) attempts to embrace the effects of the physical layer impairments, to introduce them in a multicriterium optimization and planning process. This paper contributes in this field by the proposal and comparative evaluation of two novel offline impairment aware planning algorithms for transparent optical networks, which share a common QoT evaluation function. The first algorithm is based on an iterative global search driven by a set of binary integer linear programming formulations. Heuristic techniques are included to limit the binary programming complexity. The second algorithm performs different pre-orderings of the lightpath demand, followed by a sequential processing of the lightpath demands. The performance and the scalability of both approaches are investigated. Results reveal great scalability properties of the global search algorithm, and a performance similar to or better than the sequential schemes.

This study investigates the effects of including patients’ clinical information on the performance of deep learning (DL) classifiers for disease location in chest X-ray images. Although current classifiers achieve high performance using chest X-ray images alone, consultations with practicing radiologists indicate that clinical data is highly informative and essential for interpreting medical images and making proper diagnoses. In this work, we propose a novel architecture consisting of two fusion methods that enable the model to simultaneously process patients’ clinical data (structured data) and chest X-rays (image data). Since these data modalities are in different dimensional spaces, we propose a spatial arrangement strategy, spatialization, to facilitate the multimodal learning process in a Mask R-CNN model. We performed an extensive experimental evaluation using MIMIC-Eye, a dataset comprising different modalities: MIMIC-CXR (chest X-ray images), MIMIC IV-ED (patients’ clinical...

Analyzing medical volume datasets requires interactive visualization so that users can extract anatomo-physiological information in real-time. Conventional volume rendering systems rely on 2D input devices, such as mice and keyboards, which are known to hamper 3D analysis as users often struggle to obtain the desired orientation that is only achieved after several attempts. In this paper, we address which 3D analysis tools are better performed with 3D hand cursors operating on a touchless interface comparatively to a 2D input devices running on a conventional WIMP interface. The main goals of this paper are to explore the capabilities of (simple) hand gestures to facilitate sterile manipulation of 3D medical data on a touchless interface, without resorting on wearables, and to evaluate the surgical feasibility of the proposed interface next to senior surgeons (N = 5) and interns (N = 2). To this end, we developed a touchless interface controlled via hand gestures and body postures t...

A residual dispersion compensating octagonal photonic crystal fiber (OPCF), with an elliptical array of circular airholes in the fiber core region, is proposed. The full-vector finiteelement method with perfectly matched layer boundary is used as the analysis tool. It is demonstrated that it is possible to obtain large average negative dispersion of -562.52 ps/(nm • km) over 240 nm and -369.10 ps/(nm • km) over 630 nm wavelength bands for the fast and the slow axis, respectively. In addition to large negative dispersion, ultra-high birefringence, high nonlinearity, and zero-dispersion wavelengths with low confinement loss are also warranted. The proposed OPCFs would be a promising candidate for residual dispersion compensation, supercontinuum generation, and other applications.

The last few decades have seen the emergence of forensic imaging, both clinical and post-mortem. Year after year, the scientific community has refined the radiological tools that can be used for post-mortem and clinical forensic purposes. As a result, scientific societies have published recommendations that are essential for the daily work of forensic imaging.
This third part of the review of the current state of forensic imaging describes these recommended radiological tools and also presents an overview of the various international guidelines dealing with post mortem imaging that can be found in the literature or that have been written by scientific societies.

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

"Introduction: Magnetic Resonance Spectroscopy (MRS) is a non-invasive imaging modality used to quantify brain metabolites, aiding in the diagnosis of neurological disorders. Optimization of acquisition parameters, especially Repetition Time (TR) and Echo Time (TE), is critical for enhancing signal-to-noise ratio (SNR) and metabolite detection.
Method: This six-month study involved 100 participants undergoing brain MRS at two tertiary care centers. MRS examinations were performed using a 1.5 Tesla scanner with singlevoxel PRESS sequences. TR values (1500–2000 ms) and TE values (30 ms, 144 ms) were varied systematically to assess their impact on SNR, spectral resolution (FWHM), and metabolite detection. Statistical analysis included ANOVA and correlation studies.
Results: Longer TR values significantly improved SNR (12.3 ± 1.8 at TR = 1500 ms vs. 14.7 ± 2.1 at TR = 2000 ms; p <0.001). Higher TE values enhanced spectral resolution (FWHM: 0.050 ± 0.005 ppm at TE = 30 ms vs. 0.045 ± 0.004 ppm at TE = 144 ms; p <0.01). Diagnostic accuracy was highest for brain tumors (90%). TR and SNR showed a strong positive correlation (r = 0.851; p <0.001).
Conclusion: Optimized TR and TE values significantly enhance metabolite quantification and diagnostic accuracy in MRS, particularly for brain tumors and neurodegenerative diseases."

A discrete Fourier transform ͑DFT͒ based algorithm for solving a quadratic cost functional is proposed; this regularized functional allows one to obtain a consistent gradient field from an inconsistent one. The calculated consistent gradient may then be integrated by use of simple methods. The technique is presented in the context of the phase-unwrapping problem; however, it may be applied to other problems, such as shapes from shading ͑a robot-vision technique͒ when inconsistent gradient fields with irregular domains are obtained. The regularized functional introduced here has advantages over existing techniques; in particular, it is able to manage complex irregular domains and to interpolate over regions with invalid data without any smoothness assumptions over the rest of the lattice, so that the estimation error is reduced. Furthermore, there are no free parameters to adjust. The DFT is used to compute a preconditioner because there is highly efficient hardware to perform the calculations and also because it may be computed by optical means.

A robust procedure for analyzing fringe patterns obtained from speckle interferometric techniques is proposed. The fringes generally are observed only in a region S of a rectangular lattice L. We give a method for computing ͑from S͒ the region R, where the unwrapped phase is to be computed; this computation is done by use of a morphological filter ͑in particular, a closing filter͒. We then use a fast-unwrapping algorithm to compute the phase: a preconditioned conjugate-gradient algorithm that uses the discrete Fourier transform.

This book is written as a system-based clinical-radiological review providing images from the latest available imaging modalities and covers all major diseases that are encountered in everyday clinical practice. A problem-orientated approach is used. Each chapter contains a collection of clinical cases each with a short clinical description and initial imaging followed by pertinent questions regarding the imaging findings (colour coded in red outline). The second part of each chapter contains the case diagnosis, a discussion of the role of imaging in the presenting problem, a recommended sequence for further imaging evaluation, and illustrative examples of the same disease using different imaging modalities for further investigation. Images of conditions in the differential diagnosis are also provided (colour coded in blue outline). This book is written by experienced radiologists currently working in undergraduate and postgraduate medical education. The cases are a collection of their illustrative teaching material.

Background: Intestinal wall thickening with a mass-like appearance often raises suspicion for malignancy. However, inflammatory and lymphoproliferative disorders can present similarly, leading to diagnostic challenges. Case Presentation: We report two cases of intestinal pseudo-tumoral masses with distinct etiologies. The first case involved a 30-year-old male presenting with chronic abdominal pain and bowel disturbances. Imaging revealed a circumferential thickening of the ileocecal region, mimicking a stenosing mass. A right hemicolectomy was performed, and histopathology confirmed Crohn's disease in an acute flare. The second case concerned a 43-year-old diabetic male with chronic abdominal pain and subocclusive episodes, progressing to acute intestinal obstruction. Imaging and intraoperative findings revealed an infiltrative mass in the terminal ileum. Histopathological analysis confirmed a B-cell marginal zone lymphoma. Conclusion: These cases highlight the importance of considering inflammatory and lymphoproliferative disorders in the differential diagnosis of intestinal masses. A multidisciplinary approach combining imaging, endoscopy, and histopathology is essential for accurate diagnosis and appropriate management.

FT-IR attenuated total reflection (ATR) spectroscopy was applied to quantitatively determine the extent of bovine serum albumin adsorbed onto a biomedical-grade poly(ether)urethane film deposited on a ZnSe internal reflection element (IRE). The method of adsorption density determination was based on the optical principles for a stratified medium consisting of three layers. The spectral peak area due to bulk solution was less than 1% of total peak area. The measured adsorption density of albumin in a flowing system was 3.9 μg/cm2 at a solution concentration of 4.5 g/100 mL.

The experimental demonstration of radio-over-fiber Wimedia-defined OFDM ultrawide band (OFDM-UWB) wireless transmission in fiber-to-the-home (FTTH) networks using standard single-mode fiber with lengths ranging from 25 to 100 km is reported in this paper. The transmission performance of two multichannel UWB configurations, comprising three and five OFDM channels with QPSK and BPSK modulation per carrier respectively, is evaluated. Both configurations transmit 1.56 Gbit/s aggregated bit rate, suitable for integrated optical and wireless high definition video distribution in FTTH networks. The experimental results show that an increased transmission reach can be achieved if the lower number of OFDM-UWB channels at higher bit rate per channel configuration is employed. U LTRAWIDE band (UWB) wireless technology is experi- encing a fast market introduction targeting low-cost shortrange high bit rate cabling replacement for high-definition television (HDTV) audio/video. A large number of HDTV audio/ video wireless solutions based on UWB technology have appeared in the market very recently . Moreover, consumer UWB-enabled HDTV receivers, like [2], are being introduced in the market, which reveals UWB as the technology of choice for low-cost wireless HDTV connectivity. Fiber-based access, also known as fiber-to-the home (FTTH) networks, is also at deployment stage nowadays . The

In this paper, we propose and experimentally demonstrate a simple, cost-effective hybrid gigabit fiber-wireless system for in-building wireless access. Simplicity and cost-effectiveness are achieved in all parts of the system by utilizing direct laser modulation, optical frequency up-conversion, combined single mode/multimode fiber transmission and envelope detection. Error-free transmission of 2-Gbps data in 60-GHz band over a composite channel including 10-km standard single-mode fiber (SSMF)/1-km multimode fiber (MMF) and 6.5-m air transmission was successfully achieved.

A 25-Gb/s OFDM 60-GHz radio over fiber (RoF) transmission system employing a gain switched DFB laser for millimeter-wave generation is demonstrated. Transmission performance below the 7% FEC limit is achieved over 50 km of fiber initially by employing precompensation. This precompensation overcomes phase noise caused by the optical phase decorrelation induced by chromatic dispersion on the two optical channels separated by 60 GHz. An externally injected gain switched laser is subsequently employed to eradicate the need for the precompensation, thus reducing phase noise and increasing the tolerance to the induced time delay between the optical tones. Transmission performance below the 7% limit is achieved over 25 km of fiber with 2-m wireless transmission in this case.

We propose and experimentally demonstrate an optical wireless DWDM system at 60 GHz with optical incoherent heterodyne up-conversion using an optical frequency comb. Multiple users with wireline and wireless services are simultaneously supported.

The experimental demonstration of radio-over-fiber Wimedia-defined OFDM ultrawide band (OFDM-UWB) wireless transmission in fiber-to-the-home (FTTH) networks using standard single-mode fiber with lengths ranging from 25 to 100 km is reported in this paper. The transmission performance of two multichannel UWB configurations, comprising three and five OFDM channels with QPSK and BPSK modulation per carrier respectively, is evaluated. Both configurations transmit 1.56 Gbit/s aggregated bit rate, suitable for integrated optical and wireless high definition video distribution in FTTH networks. The experimental results show that an increased transmission reach can be achieved if the lower number of OFDM-UWB channels at higher bit rate per channel configuration is employed. U LTRAWIDE band (UWB) wireless technology is experi- encing a fast market introduction targeting low-cost shortrange high bit rate cabling replacement for high-definition television (HDTV) audio/video. A large number of HDTV audio/ video wireless solutions based on UWB technology have appeared in the market very recently . Moreover, consumer UWB-enabled HDTV receivers, like [2], are being introduced in the market, which reveals UWB as the technology of choice for low-cost wireless HDTV connectivity. Fiber-based access, also known as fiber-to-the home (FTTH) networks, is also at deployment stage nowadays . The

In this paper, the feasibility of the joint distribution of ultra-wideband (UWB) and WIMAX wireless using polarization multiplexing as a coexistence technique is proposed and experimentally demonstrated within the framework of passive optical networks (PON). Four single-and orthogonal-polarization multiplexing schemes are studied targeting to reduce the mutual interference when UWB and WiMAX are distributed jointly through standard single-mode fiber (SSMF) without transmission impairments compensation techniques and amplification. Experimental results indicate successful transmission up to 25 km, in SSMF exceeding the range in typical PON deployments. The radio link penalty introduced by optical transmission is also investigated in this paper. Index Terms-Optical fiber communication, radio-over-fiber, polarization division multiplexing, integrated optical-wireless access, ultra-wideband radio, WiMAX radio I. INTRODUCTION assive optical networks (PON) are a fiber-to-the-home (FTTH) access technology of special interest nowadays under deployment around the world [1] . PON access the customer premises employing repeater-less optical power splitting and standard single-mode fiber (SSMF). PON technology is preferred when areas with a larger number of users must be served . PON leads to a more economical network deployment than other point-to-point optical access technologies due to several factors: (i) Transmission impairments, such as group-velocity dispersion (GVD) or polarization-mode dispersion (PMD), are not required to be compensated in most cases . (ii) User aggregation is done by passive splicing new fibers, giving more flexibility and scalability than optical access networks with in-line amplification, which would require careful network planning . (iii)Fiber breaks can be easily repaired, reducing maintenance costs. Nevertheless, the straightforward Manuscript

Contrast agents in dynamic contrast enhanced magnetic resonance imaging allow to localize tumors and observe their contrast kinetics, which is essential for cancer characterization and respective treatment decision-making. However, contrast agent administration is not only associated with adverse health risks, but also restricted for patients during pregnancy, and for those with kidney malfunction, or other adverse reactions. With contrast uptake as key biomarker for lesion malignancy, cancer recurrence risk, and treatment response, it becomes pivotal to reduce the dependency on intravenous contrast agent administration. To this end, we propose a multi-conditional latent diffusion model capable of acquisition time-conditioned image synthesis of DCE-MRI temporal sequences. To evaluate medical image synthesis, we additionally propose and validate the Fréchet radiomics distance as an image quality measure based on biomarker variability between synthetic and real imaging data. Our results demonstrate our method's ability to generate realistic multi-sequence fat-saturated breast DCE-MRI and uncover the emerging potential of deep learning based contrast kinetics simulation. We publicly share our accessible codebase at and provide a user-friendly library for Fréchet radiomics distance calculation at .

Abstract: Hybrid PLC-VLC systems have generated a lot of research attention lately due to high data speeds and low implementation costs they offer. Owing to the increased number of devices connected to the internet, there has been an abrupt rise of data congestion in the RF spectrum, hence there is need to relieve it to allow high speed data communication access. Research output has provided evidence that PLC and VLC technologies can be integrated successfully to provide an alternate and cost-effective solution to relieve the RF spectrum...M.Ing. (Electrical and Electronic Engineering Science

This article describes an enhanced curvature pattern based melanoma diagnosis system using convolution techniques and ensemble classifiers. We extract the 3D data of melanoma with a photometric stereo device first. Then differential forms of the melanoma surface can be extracted with the convolution method proposed. After extracting 3D based differential forms, statistical moments of enhanced principal curvatures of skin surfaces are calculated to describe the geometrical texture patterns. Finally, ensemble classifiers are constructed whose optimal mean sensitivity and specificity can reach 89.24 percent and 87.62 percent respectively. Comparisons with skin tilt/slant pattern based 3D shape characterization method and 2D methods like color variation and border irregularity are also included.

Purpose: Quantitative Transmission (QT) ultrasound has shown promise as a breast imaging modality. This study characterizes the performance of the latest generation of QT ultrasound scanners: QT Scanner 2000. Methods: The scanner consists of a 2048-element ultrasound receiver array for transmission imaging and three transceivers for reflection imaging. Custom fabricated phantoms were used to quantify the imaging performance parameters. The specific performance parameters that have been characterized are spatial resolution (as point spread function), linear measurement accuracy, contrast to noise ratio, and image uniformity, in both transmission and reflection imaging modalities. Results: The intrinsic in-plane resolution was measured to be better than 1.5 mm and 1.0 mm for transmission and reflection modalities respectively. The linear measurement accuracy was measured to be, on average, approximately 1% for both the modalities. Speed of sound image uniformity and measurement accuracy were calculated to be 99.5% and <0.2% respectively. Contrast to noise ratio (CNR) measurements vary as a function of object size. Conclusions: The results show an improvement in the imaging performance of the system in comparison to earlier ultrasound tomography systems, which are applicable to clinical applications of the system, such as breast imaging.

We report studies on UV-photobleached optical channel waveguides in nonlinear optical polymer films. The nonlinear optical polymer used is poly1methyl methacrylate2@DR1 side-chain polymer. The effective indices of the channel waveguides are measured with the prism-coupling technique, along with the effective indices of bleached and unbleached polymer films. The effective-index method was used to predict the effective indices of the channel waveguides from measurements of the slab waveguides, without detailed knowledge of the index distributions in the polymer films. Some local stress-related effects on the boundaries of the channel waveguides caused by the UV-bleaching process are identified by comparison between direct channel measurement and prediction. It is found that the technique used in this study can be employed to predict the performance of channel waveguides processed such that they have no excessive internal stress distributions. In a UV-photobleached polymer waveguide, the way of describing the index distribution can be simplified The authors are with the Department of Electrical and Computer Engineering,

One of the most efficient ways to prepare nonlinear optical polymer channel waveguides is by photobleaching. To control the index profile precisely and to design and improve the performance of active electro-optical devices, modeling of the photobleaching process is important. We report our phenomenological bleaching model, which uses a stretched exponential time dependency technique that predicts the index profile for polymer channel waveguides and present design rules for active optical switches and modulators. One way to verify the bleaching model is to calculate the effective index and compare this with our measured effective index obtained with prism-coupling techniques. The bleaching model shows good agreement with experiments.

Purpose-Total body fat, lean, and bone mineral content (BMC) in addition to regional fat and lean mass values for arms, legs, and trunk were compared across a pencil-beam (Lunar DPX-L) and two fan-beam (GE Lunar Prodigy and GE Lunar iDXA) dual energy x-ray absorptiometry (DXA) systems. Methods-Subjects were a multi-ethnic sample of 99 healthy adult males (47%) and females (mean ± SD: age 46.3 ± 16.9 yrs; weight 73.4±16.6 kg; height 167.6±9.7 cm; BMI 26.0±5.2 kg/m 2 ) who had whole-body scans performed within a 3 hour period on the three systems. Repeated measures ANOVA was used to test the null hypothesis that the mean values for the three systems were equal. Translation equations between the methods were derived using regression techniques. For both genders, total BMC by iDXA was lower (P≤0.004) than the other systems. Lean: For males, iDXA was lower (P≤0.03) than the other systems for total, trunk and arms. For females, DPXL estimated higher (P<0.001) lean mass compared to the other systems for total, trunk and arms, but iDXA estimated greater legs lean mass. For both genders, all DPXL mean values were greater than Prodigy mean values (P<0.001). Fat: In females, all 3 systems were different from each other for total, trunk, and legs (P≤0.04). For arms, DPXL and iDXA were higher than Prodigy (P<0.0004). For males, DPXL was less (P<0.001) for total body, trunk and legs compared to the other two systems and greater than Prodigy only for arms (P<0.0007). These data were used to derive translation equations between systems. For several measurements, the differences between systems were related to gender. Conclusion-For estimation of BMC and body composition, there was high agreement between all DXA systems (R 2 =0.85 to 0.99). Even so, cross-calibration equations should be used to examine data across systems to avoid erroneous conclusions.

Continuous testing at room temperature of large optics made of Zerodur has revealed a delayed elastic effect under low stress levels during both load and recovery after removal. Using a high-performance mechanical profilometer, a delayed strain of the order of 1% is realized over a period of a few weeks. The time-dependent phenomenon is elastic and reversible, but must be accounted for in various applications of optical design.

We present a radiomics-based approach developed for the SPIE-AAPM-NCI PROSTATEx challenge. The task was to classify clinically significant prostate cancer in multiparametric (mp) MRI. Data consisted of a "training dataset" (330 suspected lesions from 204 patients) and a "test dataset" (208 lesions/140 patients). All studies included T2-weighted (T2-W), proton density-weighted, dynamic contrast enhanced, and diffusionweighted imaging. Analysis of the images was performed using the MIM imaging platform (MIM Software, Cleveland, Ohio). Prostate and peripheral zone contours were manually outlined on the T2-W images. A workflow for rigid fusion of the aforementioned images to T2-W was created in MIM. The suspicious lesion was outlined using the high b-value image. Intensity and texture features were extracted on four imaging modalities and characterized using nine histogram descriptors: 10%, 25%, 50%, 75%, 90%, mean, standard deviation, kurtosis, and skewness (216 features). Three classification methods were used: classification and regression trees (CART), random forests, and adaptive least absolute shrinkage and selection operator (LASSO). In the held out by the organizers test dataset, the areas under the curve (AUCs) were: 0.82 (random forests), 0.76 (CART), and 0.76 (adaptive LASSO). AUC of 0.82 was the fourth-highest score of 71 entries (32 teams) and the highest for feature-based methods.

Advances in optical designs are enabling the development of miniature microscopes that can examine tissue in situ for early anatomic and molecular indicators of disease, in real time, and at cellular resolution. These new devices will lead to major changes in how diseases are detected and managed, driving a shift from today's diagnostic paradigm of biopsy followed by histopathology and recommended therapy, to non-invasive point-of-care diagnosis with possible same-session definitive treatment. This shift may have major implications for the training requirements of future physicians to enable them to interpret real-time in vivo microscopic data, and will also shape the emerging fields of telepathology and telemedicine. Implementation of new technologies into clinical practice is a complex process that requires bridging gaps between clinicians, engineers and scientists. This article provides a forward-looking discussion of these issues, with a focus on malignant and pre-malignant lesions, by first highlighting some of the clinical areas where point-of-care in vivo microscopy could address unmet needs, and then by reviewing the technological challenges that are being addressed, or need to be addressed, for in vivo microscopy to become a standard clinical tool.

This study presents a series of 13 patients who underwent peroneal tendoscopy as a solitary or accessory procedure at our department in 2013. Patients were clinically diagnosed with peroneal tendons disorders and underwent an additional radiological assessment. Peroneal tendoscopy was carried out in a standard manner before any other arthroscopic or open procedure. Postoperative management depended on the type of pathology. We found 3 peroneus brevis tendon partial tears, 4 cases of a low-lying peroneus brevis muscle belly, 5 cases of tenosynovitis, and 1 case of an intrasheath peroneal tendon subluxation. In 5 patients peroneal tendoscopy was performed as a solitary procedure and in 8 patients as an accessory procedure - together with anterior or posterior ankle arthroscopy, combined posterior and anterior ankle arthroscopy, or open surgery. Both as a solitary and accessory procedure, peroneal tendoscopy was safe and successful, ie, all patients were without any symptoms at one-yea...

Forced, time-varying ¯ames are laminar systems that help bridge the gap between laminar and turbulent combustion. In this study, we investigate computationally and experimentally the structure of an acousti-cally forced, axisymmetric laminar methane-air diffusion ¯ame in which a cylindrical fuel jet is surrounded by a co¯owing oxidizer jet. The ¯ame is forced by imposing a sinusoidal modulation on the steady fuel ¯ow rate. Rayleigh scattering and spontaneous Raman scattering of the fuel are used to generate the temperature pro®le. Particle image velocimetry (PIV) is used to measure the fuel tube exit velocity over a cycle of the forcing modulation. CH ¯ame emission measurements have been done to predict the excited-state CH (CH*) levels. Computationally, we solve the transient equations for the conservation of total mass, momentum, energy, and species mass with detailed transport and ®nite-rate C2 chemistry submodels to predict the pressure, velocity, temperature, and species concen...

The impact of gate fan-in and fan-out limits on digital circuit delay is discussed with a set of benchmark circuits. This research presents the advantages of exploiting the ability of optoelectronic gates to perform both logic operations and optical interconnections with systematic optimization. It is possible for gate-level optical interconnected optoelectronic circuits to compete with their pure silicon counterparts in terms of the combinational circuit delay and system clock rate.

Recent years have witnessed a resurgence of interest in nonlinear multimode optical systems where a host of intriguing effects have been observed that are impossible in single-mode settings 1-9 . While nonlinearity can provide a rich environment where the chaotic power exchange among thousands of modes can lead to novel behaviors, at the same time, it poses a major challenge in terms of understanding and harnessing these processes to advantage. Over the years, statistical models have been developed to macroscopically describe the response of these complex systems . One of the cornerstones of these theoretical formalisms is the prediction of a photon-photon mediated thermalization process that leads to a Rayleigh-Jeans distribution of mode occupations . Here we report the use of mode-resolved measurement techniques to make the first direct observations of thermalization to a Rayleigh-Jeans power distribution in a multimode optical fiber. We experimentally demonstrate that the underlying system Hamiltonian remains invariant during propagation while power equipartition takes place among degenerate groups of modes -all in full accord with theoretical predictions. Our results may pave the way toward a new generation of highpower optical sources whose brightness and modal content can be controlled using principles from thermodynamics and statistical mechanics 18 .

Recent years have witnessed a resurgence of interest in nonlinear multimode optical systems where a host of intriguing effects have been observed that are impossible in single-mode settings 1-9 . While nonlinearity can provide a rich environment where the chaotic power exchange among thousands of modes can lead to novel behaviors, at the same time, it poses a major challenge in terms of understanding and harnessing these processes to advantage. Over the years, statistical models have been developed to macroscopically describe the response of these complex systems . One of the cornerstones of these theoretical formalisms is the prediction of a photon-photon mediated thermalization process that leads to a Rayleigh-Jeans distribution of mode occupations . Here we report the use of mode-resolved measurement techniques to make the first direct observations of thermalization to a Rayleigh-Jeans power distribution in a multimode optical fiber. We experimentally demonstrate that the underlying system Hamiltonian remains invariant during propagation while power equipartition takes place among degenerate groups of modes -all in full accord with theoretical predictions. Our results may pave the way toward a new generation of highpower optical sources whose brightness and modal content can be controlled using principles from thermodynamics and statistical mechanics 18 .

Glass ion exchange is an attractive method for fabricating integrated optical components. We investigate the feasibility of making a single-mode glass ion-exchanged interferometer designed especially to obtain an interference pattern. The design of the interferometer is based on the use of tapered waveguides to obtain a collimated beam. This interferometer could be used as a chemical or biological sensor.

Accurate acne grading is critical in optimizing therapeutic decisions yet remains challenging due to lesion ambiguity and subjective clinical assessments. This study proposes the Feature Feedback-Based Pseudo-Label Learning (FF-PLL) framework to address these limitations through three innovations: (1) an acne feature feedback (AFF) architecture with iterative pseudo-label refinement to improve the training robustness, enhance the pseudo-label quality, and increase the feature diversity; (2) all-facial skin segmentation (AFSS) to reduce background noise, enabling precise lesion feature extraction; and (3) the AcneAugment (AA) strategy to foster model generalization by introducing diverse acne lesion representations. Experiments on the ACNE04 and ACNE-ECKH benchmark datasets demonstrate the superiority of the proposed framework, achieving accuracy of 87.33% on ACNE04 and 67.50% on ACNE-ECKH. Additionally, the model attains sensitivity of 87.31%, specificity of 90.14%, and a Youden index (YI) of 77.45% on ACNE04. These advancements establish FF-PLL as a clinically viable solution for standardized acne assessment, bridging critical gaps between computational dermatology and practical healthcare needs.