Medical Imaging

This paper reports on the use of cellulose paper simultaneously as electrolyte, separation of electrodes, and physical support of a rechargeable battery. The deposition on both faces of a paper sheet of metal or metal oxides thin layers with different electrochemical potentials, respectively as anode and cathode, such as Cu and Al, lead to an output voltage of 0.70 V and a current density that varies between 150 nA/cm 2 and 0.5 mA/cm 2 , subject to the paper composition, thickness and the degree of OH x species adsorbed in the paper matrix. The electrical output of the paper battery is independent of the electrodes thickness but strongly depends on the atmospheric relative humidity (RH), with a current density enhancement by more than 3 orders of magnitude when RH changes from 60% to 85%. Besides flexibility, low cost, low material consumption, environmental friendly, the power output of paper batteries can be adapted to the desired voltage-current needed, by proper integration. A 3-V prototype was fabricated to control the ON/OFF state of a paper transistor.

Objectives: To evaluate positron emission tomography-computed tomography (PET-CT) for the preoperative management of early-stage intermediate-and high-risk endometrial cancer (EC). Study design: Data of patients with intermediate-and high-risk early-stage EC were retrieved from a prospectively collected database. Patients with preoperative PET-CT followed by surgical staging including pelvic lymphadenectomy were analyzed. Diagnostic performance for lymph node (LN) metastasis was evaluated. Results: Overall, 45 patients were included: 27 (60%) and 18 (40%) with intermediate-and highrisk EC, respectively. Four patients (8.8%) had LN metastasis, three correctly identified at PET-CT, yielding a sensitivity of 75% (95% CI 21.9-98.7). Among 41 patients (91.2%) without LN metastasis, 38 had negative PET-CT with specificity of 92.7% (95% CI 78.9-98.1). The negative predictive value (NPV) was 97.4% (95% CI 84.9-99.9) and the positive predictive value was 50% (95% CI 13.9-86.1). Conclusions: The utility of PET-CT is limited by the low sensitivity for LN metastasis in intermediate-and high-risk early-stage EC, that may impede to consider PET-CT alone an adequate alternative to surgical retroperitoneal staging by lymphadenectomy or sentinel LN biopsy. However, the high diagnostic accuracy, specificity and NPV might support its adoption to improve the diagnostic accuracy of the sentinel LN algorithm.

The maximum distance to which the secondary mirror can be moved with respect to its primary in a true Cassegrain telescope with limited image deterioration is found to be proportional to the fourth power of the focal ratio of the primary mirror. This limit is independent of all other parameters describing the system when the magnification of the secondary is greater than about 3.

It is shown that the Fraunhofer diffraction pattern of a tilted aperture screen can be interpreted as a ' monocular view of the Ewald sphere. Two of those patterns recorded at opposite tilting angles are used to give a stereoscopic impression of the Ewald sphere. Experimental results are shown, and the approximations involved are discussed.

An hybrid atomic force-scanning near-field optical microscope (AFM-SNOM) has been realized starting from a home-built AFM. The instrument uses a tetrahedral SiN tip for force and near field detection and is designed to provide, besides simple imaging, a full three-dimensional (3-D) mapping of force, friction and light intensity on the sample. High-resolution optical images of dielectric samples are presented together with curves describing the behavior of the collected optical intensity as a function of tip-object distance. AFM images and forcedistance curves are reported as well and are compared with those obtained from the optical channel. Subwavelength features of the samples can be easily appreciated in both kinds of images, and the refractive index of the object can be computed from the attenuation constant of the tunneling light detected by the tip, with the AFM curve providing a convenient way of detecting the contact point. The spatial resolution of this kind of measurement is far better than that obtainable with any other index-measuring device. Homogeneous glass samples as well as monomode channel waveguides were analyzed in our experiments. The refractive index of several different prisms, made either of BK7 (n = 1:519 at = 532 nm) or of SF58 (n = 1:932) glass, could be measured with our near-field technique. As for the channel waveguides, the accuracy of our measurements lets us detect their presence and lateral extension in the substrate but is not yet sufficient to allow the reconstruction of their index profile.

A theory is presented which relates the minimum detectable contrast level for an object in the presence of noise to the statistics of the speckle. Consideration is given to smoothing of the noise by multiple looks and by area. Measurements of the minimum detectable contrast are made for two types of speckle noise. First, a coherent, plane wave is added to an ideal diffuse wave and the threshold of detection is established as a function of the beam ratio. Secondly, these results are compared to the technique of speckle smoothing using an N-fold intensity superposition of fully developed theory is observed.

In Low and Middle-Income Countries (LMICs), efforts to eliminate the Tuberculosis (TB) epidemic are challenged by the persistent social inequalities in health, the limited number of local healthcare professionals, and the weak healthcare infrastructure found in resource-poor settings. The modern development of computer techniques has accelerated the TB diagnosis process. In this paper, we propose a novel method using Convolutional Neural Network(CNN) to deal with unbalanced, less-category X-ray images. Our method improves the accuracy for classifying multiple TB manifestations by a large margin. We explore the effectiveness and efficiency of shuffle sampling with cross-validation in training the network and find its outstanding effect in medical images classification. We achieve an 85.68% classification accuracy in a large TB image dataset, surpassing any state-of-art classification accuracy in this area. Our methods and results show a promising path for more accurate and faster TB diagnosis in LMICs healthcare facilities.

Although current literature abounds in a variety of edge detection algorithms, they do not always lead to acceptable results in extracting various features in an image. In this paper, we address the problem of detecting blood vessels in retinal images. Blood vessels nsually have poor local contrast and the application of existing edge detection algorithms yield results which are not satisfactory. We introduce an operator for feature extraction based on the optical and spatial properties of objects to be recognized. The gray-level profile of the cross section of a blood vessel is approximated by a Gaussian shaped curve. The concept of matched filter detection of signals is used to detect piecewise linear segments of blood vessels in these images. We construct 12 different templates that are used to search for vessel segments along all possible directions. We discuss various issues related to the implementation of these matched filters. The results are compared to those obtained with other methods. The automatic detection of blood vessels in the retina could help physicians in diagnosing ocular diseases.

A theory of the influence of measurement conditions on temperature measurement accuracy with infrared systems has been recently presented. A comparison study of the shortwave 13-5-µm2 and longwave 18-12-µm2 measuring IR cameras was conducted on the basis of this theory. The results of the simulations show that the shortwave systems in typical measurement conditions generally offer better accuracy in temperature measurement than do the longwave systems. Some experiments that use a commercially available IR camera were carried out to verify the theory. The results of these experiments and a discussion about the theory limitations are presented.

Combining both spatial and intensity information in image, we present an MRI brain image segmentation approach based on multiresolution edge detection, region selection, and intensity threshold methods. The detection of white matter structure in brain is emphasized in this paper. First, a multi-resolution brain image representation and segmentation procedure based on a multi-scale image filtering method is presented. Given the nature of the structural connectivity and intensity homogeneity of brain tissues, region-based methods such as region growing and subtraction to segment the brain tissue structure from the multi-resolution images are utilized. From the segmented structure, the region-of-interest (ROI) image in the structure region is derived, and then a modified segmentation of the ROI based on an automatic threshold method using our threshold selection criterion is presented. Examples on both T1 and T2 weighted MRI brain image segmentation is presented, showing finer brain tissue structures. ᭧

We propose a new hierarchical approach to resolution scalable lossless and near-lossless (NLS) compression. It combines the adaptability of DPCM schemes with new hierarchical oriented predictors to provide resolution scalability with better compression performances than the usual hierarchical interpolation predictor or the wavelet transform. Because the proposed hierarchical oriented prediction (HOP) is not really efficient on smooth images, we also

In the modern world, people are beliving videos as part of social communication; as camera editing
techniques are advanced, video doctoring is a technique for editing and recreating new details in the footage.
Identifying these doctored videos poses a problem for the media source, the court of law, and the framework of
evidence service. The research on video forensics, and specifically on the automatic recognition of object-based
detection of video forgery, is still in its infancy. The approach proposed in this paper uses noise properties,
extracted from each frame of the video using Wavelet Transform and nonlinear thresholding such as optimal
SURE shrinkage. Gaussian Mixture Density (GMD) uses this as a Gaussian classifier, and the ExpectationMaxima algorithm sets the GMD parameter. Results of the output matrix show that we get excellent precision
99.36 percent recall 99.80 and precision 97.34 percent respectively for object removal and frame duplication
detection compared to subsisting methods. The proposed approach effectively detects traces in the forensic video
dataset and recognizes these.

A coherent processor is presented which is capable of performing a large class of 1-D linear space-variant operations. The only components of the processor are a 1-D input, a mask whose transmittance is specified by the desired linear operation, and an output plane. Compared with other 1-D processors, this processor has advantages of real space compactness and total elimination of vignetting. Experimental results are presented for the specific operations of convolution and spectrum scaling.

An experiment to investigate the potential of a laser-induced plasma method for determining concrete compressive strength was conducted by focusing a Nd:YAG laser on concrete samples with different degrees of compressive strength. This technique was developed in light of the role of the shock wave in the generation of a laser-induced plasma. It was found that the speed of the shock front depends on the hardness of the sample. It was also found that a positive relationship exists between the speed of the shock front and the ionization rate of the ablated atoms. Hence, the ratio of the intensity between the Ca(II) 396.8 nm and Ca(I) 422.6 nm emission lines detected from the laser-induced plasma can be used to examine the hardness of the material. In fact, it was observed that the ratio changes with respect to the change in the concrete compressive strength. The findings also show that the ratio increases with time after the cement is mixed with water.

We compared four automated methods for hippocampal segmentation using different machine learning algorithms (1) hierarchical AdaBoost, (2) Support Vector Machines (SVM) with manual feature selection, (3) hierarchical SVM with automated feature selection (Ada-SVM), and (4) a publicly available brain segmentation package (FreeSurfer). We trained our approaches using T1weighted brain MRI's from 30 subjects (10 normal elderly, 10 mild cognitive impairment (MCI), and 10 Alzheimer's disease (AD)), and tested on an independent set of 40 subjects (20 normal, 20 AD). Manually segmented gold standard hippocampal tracings were available for all subjects (training and testing). We assessed each approach's accuracy relative to manual segmentations, and its power to map AD effects. We then converted the segmentations into parametric surfaces to map disease effects on anatomy. After surface reconstruction, we computed significance maps, and overall corrected p-values, for the 3D profile of shape differences between AD and normal subjects. Our AdaBoost and Ada-SVM segmentations compared favorably with the manual segmentations and detected disease effects as well as FreeSurfer on the data tested. Cumulative pvalue plots, in conjunction with the False Discovery Rate method, were used to examine the power of each method to detect correlations with diagnosis and cognitive scores. We also evaluated how segmentation accuracy depended on the size of the training set, providing practical information for future users of this technique.

An external reflection scanning near-field optical microscope with shear force regulation of the tip-surface distance is described. Near-field optical and shear force topographical images are compared for various samples. It is shown that the most important correlative relationships between these images can be deduced from symmetry considerations. The possibility of extracting additional information from the optical images is demonstrated on images of human blood cells.

With the introduction of spectral-domain optical coherence tomography (OCT), much larger image datasets are routinely acquired compared to what was possible using the previous generation of time-domain OCT. Thus, the need for 3-D segmentation methods for processing such data is becoming increasingly important. We report a graph-theoretic segmentation method for the simultaneous segmentation of multiple 3-D surfaces that is guaranteed to be optimal with respect to the cost function and that is directly applicable to the segmentation of 3-D spectral OCT image data. We present two extensions to the general layered graph segmentation method: the ability to incorporate varying feasibility constraints and the ability to incorporate true regional information. Appropriate feasibility constraints and cost functions were learned from a training set of 13 spectral-domain OCT images from 13 subjects. After training, our approach was tested on a test set of 28 images from 14 subjects. An overall mean unsigned border positioning error of 5 69 2 41 m was achieved when segmenting seven surfaces (six layers) and using the average of the manual tracings of two ophthalmologists as the reference standard. This result is very comparable to the measured interobserver variability of 5 71 1 98 m.

We present a model of energy consumption in IP networks. Using this model, we identify energy ldquohotspotsrdquo and estimate how energy consumption will grow with increasing network capacity. Todaypsilas Internet uses less than 1% of the available electricity supply. However, network energy consumption could grow substantially as access rates increase.

Skin diseases are among the most common health problems worldwide. In this article we proposed a method that uses computer vision based techniques to detect various kinds of dermatological skin diseases. We have used different types of image processing algorithms for feature extraction and feed forward artificial neural network for training and testing purpose. The system works on two phases- first pre-process the colour skin images to extract significant features and later identifies the diseases. The system successfully detects 9 different types of dermatological skin diseases with an accuracy rate of 90%.

This report describes the design, implementation, evaluation and original enhancements to the Live-Wire method for 2D and 3D image segmentation. Live-Wire 2D employs a semi-automatic paradigm; the user is asked to select a few boundary points of the object to segment, to steer the process in the right direction, while the result is displayed in real time. In our implementation segmentation is extended to three dimensions by performing this process on a slice-by-slice basis. User's time and involvement is further reduced by allowing him to specify object contours in planes orthogonal to the slices. If these planes are chosen strategically, Live-Wire 3D can perform 2D segmentation in the plane of each slice automatically. This report also proposes two improvements to the original method, path heating and a new graph edge feature function based on variance of path properties along the boundary. We show that these improvements lead up to a 33% reduction in interaction with the user, and improved delineation in presence of strong interfering edges.

Most confocal microscopes do not produce images in real time with nonlaser light sources. The tandem scanning confocal microscope does produce such images but, because the pinhole apertures of the Nipkov disk must be placed far apart to reduce cross talk between neighboring pinholes, only 1% or less of the light available for imaging is used. We show that, by using aperture correlation techniques and relaxing the requirement to obtain a pure confocal image directly, one can obtain real-time confocal images with a dramatically increased (25% or even 50%) light budget.

We present a novel multi-task convolutional neural network called Multi-task SonoEyeNet (M-SEN ) that learns to generate clinically relevant visual attention maps using sonographer gaze tracking data on input ultrasound (US) video frames so as to assist standardized abdominal circumference (AC) plane detection. Our architecture consists of a generator and a discriminator, which are trained in an adversarial scheme. The generator learns sonographer attention on a given US video frame to predict the frame label (standardized AC plane / background). The discriminator further fine-tunes the predicted attention map by encouraging it to mimick the ground-truth sonographer attention map. The novel model expands the potential clinical usefulness of a previous model by eliminating the requirement of input gaze tracking data during inference without compromising its plane detection performance (Precision: 96.8, Recall: 96.2, F-1 score: 96.5).

The Fraunhofer diffraction pattern of an aperture function, which can be described in terms of the superposition of a known aperture function with a half plane, has an amplitude distribution which is real along one direction and complex along the orthogonal direction. The real and imaginary parts of the amplitude distribution are related by Hubert transforms (dispersion relations). These disper sion relations can be used to arrive at the diffraction patterns of a variety of apertures having symmetry properties. Theoretical results are presented to illustrate the diffraction pattern of various apertures.

Using our new negative Δ LC material in a fringing field switching (n-FFS) cell, we demonstrated superior performances to conventional positive Δ FFS (p-FFS) LCD in transmittance, viewing angle, cell gap sensitivity, gamma curve, while keeping a comparable operation voltage and response time. Therefore, n-FFS has potential to replace p-FFS for next-generation mobile displays.

Following the development and publication of the JCAMP-DX protocol 4.24 and its successful implementation in the field of infrared spectroscopy, data exchange without loss of information, between systems of different origin and internal format, has become a reality. The benefits of this system-independent data transfer standard have been recognized by workers in other areas who have expressed a wish for an equivalent, compatible standard in their own fields. This publication details a protocol for the exchange of Nuclear Magnetic Resonance (NMR) spectral data without any loss of information and in a format that is compatible with all storage media and computer systems. The protocol detailed below is designed for spectral data transfer, and its use for NMR imaging data transfer has not as yet been investigated.

Vincent Vaerman, my supervisor at LTS for all support, guidance and the opportunity to work with him on this exciting subject. Thank you very much also to Dr. Jean-Marc Vessin for the valuable input during the regular ERASMUS students supervision and to all other faculty and stu at LTS for the friendly reception and helpful support. Erwin Keeve for the supervision of this work for the university in Erlangen and his valuable input. Special thanks go to Luc Bidaut at the Digital Imaging Unit and Dr. Dominique Didier, both with the University hospital at Geneva for providing the MR image data and valuable tips and information. Last but not least i would like to thankfully acknowledge all the support received from my parents during my stay here.

A simple apparatus for time-correla ted single photon counting (TCSPC) m easurements in the near-infrared (near-IR) region for scanning-type applications has been constructed and examined. The apparatus consisted of ® ve m ajor com ponents including a pulsed diode laser source (lasing wavelength 5 780 nm; rep etition rate 5 80 MHz; power 5 5 mW ; pulse width 5 150 ps), an integrated m icroscope, a large-photoactive-area avalanche photodiode (APD), a TCSPC PC-board including the electron ics, and a Windows-based software package for accu mulating the¯uorescen ce decay pro® les. The instrument response function (IRF) of this assembly was found to be 460 ps, which is adequate for measuring lifetim es with t f $ 500 ps. Due to the sm all size of the device, it also allowed implem entation into scanning experim ents where lifetimes were measured. To dem onstrate this capability, we scanned a three-well microscope slide containing a near-IR dye. The decay pro® le of the near-IR dye, aluminum 2,3-naphthalocyanine, was collected and analyzed to obtain its lifetime, which was found to be 2.73 ns, in close agreement with the literature value for this particular dye. In addition, a three-dim ensional plot showing the decay pro® les (tim e vs. photocounts) and scan position of aluminum 2,3-naphthalocyaninē uorescence was acquired by scanning the m icroscope head over this three-well glass slide. In the scanning m ode, the IRFs as well as the decays of the dyes were found to be very stable. The device dem onstrated a concentration detection sensitivity of 0.44 nM; however, the dynamic range was limited due to the slow tim e constant (passive quenching) associated with the APD.

The necessary and sufficient conditions on the gain of the linear amplifier are determined under which the light output exhibits sub-Poissonian photon statistics or squeezing. It is found that for these effects the intensity gain must not exceed 2 under any circumstances. It is also shown that there exists a weaker sufficiency condition on the gain above which all nonclassical features of the field disappear. This suggests the possibility that other quantum effects may persist in the intermediate, still unexplored, domain of operation of the amplifier.

Mean-variance analysis is described as a method for characterization of the read-noise and gain of focal plane array (FPA) detectors, including charge-coupled devices (CCDs), charge-injection devices (CIDs), and complementary metal-oxide-semiconductor (CMOS) multiplexers (infrared arrays). Practical FPA detector characterization is outlined. The nondestructive readout capability available in some CIDs and FPA devices is discussed as a means for signal-tonoise ratio improvement. Derivations of the equations are fully presented to unify understanding of this method by the spectroscopic community.

We consider how absorption-induced material heating alters the phase profile, the scale, the orientation, and the Bragg matching of volume holograms. We derive theoretical equations that consider the prisming, the lensing, and the Bragg mismatching that occur during material heating and compare these with experimental observations. From our Bragg-mismatching considerations we show how both read beam angle and wavelength need to be dithered for proper compensation of volume holograms for material-heating effects. Our results indicate that material heating in volume-holographic memory systems poses a severe threat to system performance. This threat is shown to be very significant in Fourier plane holograms but only moderately significant in image plane holograms.

Detecting the position of retinal structures, including the fovea center and macula, in retinal images plays a key role in diagnosing eye diseases such as optic nerve hypoplasia, amblyopia, diabetic retinopathy, and macular edema. However, current detection methods are unreliable for infants or certain ethnic populations. Thus, a methodology is proposed here that may be useful for infants and across ethnicities that automatically localizes the fovea center and segments the macula on digital fundus images. First, dark structures and bright artifacts are removed from the input image using preprocessing operations, and the resulting image is transformed to polar space. Second, the fovea center is identified, and the macula region is segmented using the proposed dynamic identification and classification of edges (DICE) model. The performance of the method was evaluated using 1200 fundus images obtained from the relatively large, diverse, and publicly available Messidor database. In 96.1...

In this paper, we deal with the subject of cross-gain modulation (XGM) and cross-phase modulation (XPM) semiconductor optical amplifier-based wavelength conversion of optical channels carrying subcarrier multiplexing signals in a comprehensive way. The equations and models that describe the conversion process and the resulting harmonic and intermodulation distortions are obtained showing the superior performance of XPM over XGM in terms of second-and third-order distortion and contrast ratio. Experimental results for XGM-based wavelength conversion that confirm the results predicted by our theoretical models are presented, and finally, we consider the specific application of wavelength conversion of optical channels carrying full frequency plans such as that of cable television applications.

The points at which two-dimensional spectra of band-limited functions are zero can be used to generate a polynomial approximation of the complex spectrum. These point-zero locations are common to both the spectrum and the associated power spectrum. The phase of the complex-valued polynomial along with the measured intensity data is used to generate an initial guess for the function that an error-reduction algorithm can improve. This approach has practical utility for Fourier phase retrieval as well as for blind deconvolution. The limitations of the model are discussed, and examples are given.

Metal-organic semiconductor films are fabricated as co-evaporated films. It is demonstrated that the technique can be used to fabricate metalsemiconductor surface-enhanced Raman scattering (SERS) or surfaceenhanced resonance Raman scattering (SERRS) substrates or to attain SERS or SERRS of highly insoluble pigments. The experiments are carried out using three different pigments: iron phthalocyanine (FePc) and two substituted tetracaboxylic perylenes (PTCDs). The structure of the co-PVD films was characterized at the nanoscale by scanning electron microscopy through field-emission gun (SEM-FEG), revealing a fairly homogeneous spatial distribution of the silver-pigment nanoparticles. The fabricated mixed nanostructures show a homogenous distribution of plasmon enhancement as observed in the point-by-point mapping of the SERRS spectra recorded with micrometer spatial resolution in Raman microscopy.

Optical characterization of three red pigments, two organic and one inorganic, was studied in order to provide important and reliable parameters for research and applications. The pigments were C.I. Pigment Red 176, C.I. Pigment Red 57:1, and C.I. Pigment Red 101. All three pigments were used in their transparent form, that is, their radius of gyration was smaller than 250 nm. The particles were suspended in an apolar solvent and absorption, reflection, and scattering of the suspensions were measured by means of a single spectrophotometer and the effective complex refractive index was determined.

A novel fiber Bragg grating (FBG) sensing multiplexing system based on the combination of InGaAs spectrometer and Fabry-Perot (F-P) filter (InGaAs/F-P) is proposed. The multiplexing system only demodulates FBG sensors whose peak wavelengths are shifting. The demodulation can be sequenced according to each sensor's priority, latency time and wavelength shifting. What is more, the monitor section of that system is not influenced by environmental temperature and source intensity fluctuations. At the average signal repeat rate of 6Hz, the average delay time of the conventional wavelength-and spatial-division combined system, the long period grating (LPG) combined system and the InGaAs/F-P system are 303, 97, and 6 ms, respectively. Simulation analysis and experiment work demonstrated that the InGaAs/F-P system is more rational and smart than other counterparts.

This paper presents a methodology and algorithm for generating diffeomorphisms of the sphere onto itself, given the displacements of a finite set of template landmarks. Deformation maps are constructed by integration of velocity fields that minimize a quadratic smoothness energy under the specified landmark constraints. We present additional formulations of this problem which incorporate a given error variance in the positions of the landmarks. Finally, some experimental results are presented. This work has application in brain mapping, where surface data is typically mapped to the sphere as a common coordinate system.

The fixed oil of Laurus novocanariensis (previously L. azorica) contains mostly glycerides together with minor non-saponifiable compounds. The direct identification and quantitative determination of costunolide and dehydrocostuslactone, two sesquiterpene lactones components of the oil that exhibit biological activities, is described. The analysis was carried out using 13 C-NMR spectroscopy (signal acquisition with inverse gated decoupling of protons; diglyme as internal standard) without separation, derivatisation or any sample preparation.

Aim-To determine the gender using mental foramen as landmark on a panoramic radiographs in selected North Gujarat population. Objective-1. To evaluate and compare the superior border of mental foramen to lower border of mandible(S-L) and inferior border of mental foramen to lower border of mandible(I-L) value in males and females bilaterally. 2. To compare the S-L and I-L between right and left side in males and female 3. To utilize above measurements for gender determination. Materials and Method-Sixty panoramic radiographs were selected for the analysis of mental foramen. Tangents were drawn through the superior and inferior borders of the foramen (S-L and I-L respectively) and perpendicular from the tangents to the lower border of the mandible bilaterally. Digital verniar caliper was used for the distance measurement from S-L and I-L. The data obtained was tabulated and subjected to statistical analysis. Result-The analyzed data of study showed that the mean values of comparison of S-L as well as I-L in males and females were significantly higher in males as compared to females. The comparison of SL and IL on right and left side in the same patient was without any significant difference. Conclusion-The results of present study concluded a definite sexual dimorphism in the position of the mental foramen from the base of the mandible; this method can applied in mass disaster where the fragments of mandible are available.

The major limitations of precise evaluation of retinal structures in present clinical situations are the lack of standardization, the inherent subjectivity involved in the interpretation of retinal images, and intra-as well as interobserver variability. While evaluating optic disc deformation in glaucoma, these limitations could be overcome by using advanced digital image analysis techniques to generate precise metrics from stereo optic disc image pairs. A digital stereovision system for visualizing the topography of the optic nerve head from stereo optic disc images is presented. We have developed an algorithm, combining power cepstrum and zero-mean-normalized cross correlation techniques, which extracts depth information using coarse-to-fine disparity between corresponding windows in a stereo pair. The gray level encoded sparse disparity matrix is subjected to a cubic B-spline operation to generate smooth representations of the optic cup/disc surfaces and new three-dimensional (3-D) metrics from isodisparity contours. Despite the challenges involved in 3-D surface recovery, the robustness of our algorithm in finding disparities within the constraints used has been validated using stereo pairs with known disparities. In a preliminary longitudinal study of glaucoma patients, a strong correlation is found between the computer-generated quantitative cup/disc volume metrics and manual metrics commonly used in a clinic. The computer generated new metrics, however, eliminate the subjective variability and greatly reduce the time and cost involved in manual metric generation in follow-up studies of glaucoma.