The current definitive diagnosis of prostate cancer is transrectal ultrasound (TRUS) guided biopsy. However, the current procedure is limited by using 2D biopsy tools to target 3D biopsy locations. This paper presents a new method for automatic segmentation of the prostate in three-dimensional transrectal ultrasound images, by extracting texture features and by statistically matching geometrical shape of the prostate. A set of Wavelet-based support vector machines (W-SVMs) are located and trained at different regions of the prostate surface. The WSVMs capture texture priors of ultrasound images for classification of the prostate and non-prostate tissues in different zones around the prostate boundary. In the segmentation procedure, these W-SVMs are trained in three sagittal, coronal, and transverse planes. The pre-trained W-SVMs are employed to tentatively label each voxel around the surface of the model as a prostate or non-prostate voxel by the texture matching. The labeled voxels in three planes after post-processing is overlaid on a prostate probability model. The probability prostate model is created using 10 segmented prostate data. Consequently, each voxel has four labels: sagittal, coronal, and transverse planes and one probability label. By defining a weight function for each labeling in each region, each voxel is labeled as a prostate or non-prostate voxel. Experimental results by using real patient data show the good performance of the proposed model in segmenting the prostate from ultrasound images.
It is widely believed that the reflection minimum in a Kretschmann-Raether experiment results from direct coupling into surface plasmon polariton modes. Our experimental results provide a surprising discrepancy between the leakage radiation patterns of surface plasmon polaritons (SPPs) launched on a layered gold/germanium film compared to the K-R minimum, clearly challenging this belief. We provide definitive evidence that the reflectance dip in K-R experiments does not correlate with excitation of an SPP mode, but rather corresponds to a particular type of perfectly absorbing (PA) mode. Results from rigorous electrodynamics simulations show that the PA mode can only exist under external driving, whereas the SPP can exist in regions free from direct interaction with the driving field. These simulations show that it is possible to indirectly excite propagating SPPs guided by the reflectance minimum in a K-R experiment, but demonstrate the efficiency can be lower by more than a factor of 3. We find that optimal coupling into the SPP can be guided by the square magnitude of the Fresnel transmission amplitude.
We aim to build the simplest possible model capable of detecting long, noisy contours in a cluttered visual scene. For this, we model the neural dynamics in the primate primary visual cortex in terms of a continuous director field that describes the average rate and the average orientational preference of active neurons at a particular point in the cortex. We then use a linear-nonlinear dynamical model with long range connectivity patterns to enforce long-range statistical context present in the analyzed images. The resulting model has substantially fewer degrees of freedom than traditional models, and yet it can distinguish large contiguous objects from the background clutter by suppressing the clutter and by filling-in occluded elements of object contours. This results in high-precision, high-recall detection of large objects in cluttered scenes. Parenthetically, our model has a direct correspondence with the Landau - de Gennes theory of nematic liquid crystal in two dimensions.
Establishing genotype-phenotype relationship is the key to understand the molecular mechanism of phenotypic adaptation. This initial step may be untangled by analyzing appropriate ancestral molecules, but it is a daunting task to recapitulate the evolution of non-additive (epistatic) interactions of amino acids and function of a protein separately. To adapt to the ultraviolet (UV)-free retinal environment, the short wavelength-sensitive (SWS1) visual pigment in human (human S1) switched from detecting UV to absorbing blue light during the last 90 million years. Mutagenesis experiments of the UV-sensitive pigment in the Boreoeutherian ancestor show that the blue-sensitivity was achieved by seven mutations. The experimental and quantum chemical analyses show that 4,008 of all 5,040 possible evolutionary trajectories are terminated prematurely by containing a dehydrated nonfunctional pigment. Phylogenetic analysis further suggests that human ancestors achieved the blue-sensitivity gradually and almost exclusively by epistasis. When the final stage of spectral tuning of human S1 was underway 45–30 million years ago, the middle and long wavelength-sensitive (MWS/LWS) pigments appeared and so-called trichromatic color vision was established by interprotein epistasis. The adaptive evolution of human S1 differs dramatically from orthologous pigments with a major mutational effect used in achieving blue-sensitivity in a fish and several mammalian species and in regaining UV vision in birds. These observations imply that the mechanisms of epistatic interactions must be understood by studying various orthologues in different species that have adapted to various ecological and physiological environments.
Atomically thin monolayer transition metal dichalcogenides possess coupling of spin and valley degrees of freedom. The chirality is locked to identical valleys as a consequence of spin–orbit coupling and inversion symmetry breaking, leading to a valley analog of the Zeeman effect in presence of an out-of-plane magnetic field. Owing to the inversion symmetry in bilayers, the photoluminescence helicity should no longer be locked to the valleys. Here we show that the Zeeman splitting, however, persists in 2H-MoTe2 bilayers, as a result of an additional degree of freedom, namely the layer pseudospin, and spin–valley-layer locking. Unlike monolayers, the Zeeman splitting in bilayers occurs without lifting valley degeneracy. The degree of circularly polarized photoluminescence is tuned with magnetic field from −37% to 37%. Our results demonstrate the control of degree of freedom in bilayer with magnetic field, which makes bilayer a promising platform for spin-valley quantum gates based on magnetoelectric effects.
by
Susan LeGendre-McGhee;
Photini S. Rice;
R. Andrew Wall;
Kyle J. Sprute;
Ramireddy Bommireddy;
Amber M. Luttman;
Raymond B. Nagle;
Edward R. Abril;
Katrina Farrell;
Chiu-Hsieh Hsu;
Denise J. Roe;
Eugene W. Gerner;
Natalia A. Ignatenko;
Jennifer K. Barton
Optical coherence tomography (OCT) is a high-resolution, nondestructive imaging modality that enables time-serial assessment of adenoma development in the mouse model of colorectal cancer. In this study, OCT was utilized to evaluate the effectiveness of interventions with the experimental antitumor agent α-difluoromethylornithine (DFMO) and a nonsteroidal anti-inflammatory drug sulindac during early [chemoprevention (CP)] and late stages [chemotherapy (CT)] of colon tumorigenesis. Biological endpoints for drug interventions included OCT-generated tumor number and tumor burden. Immunochistochemistry was used to evaluate biochemical endpoints [Ki-67, cleaved caspase-3, cyclooxygenase (COX)-2, β-catenin]. K-Ras codon 12 mutations were studied with polymerase chain reaction-based technique. We demonstrated that OCT imaging significantly correlated with histological analysis of both tumor number and tumor burden for all experimental groups (P < 0.0001), but allows more accurate and full characterization of tumor number and burden growth rate because of its time-serial, nondestructive nature. DFMO alone or in combination with sulindac suppressed both the tumor number and tumor burden growth rate in the CP setting because of DFMO-mediated decrease in cell proliferation (Ki-67, P < 0.001) and K-RAS mutations frequency (P = 0.04). In the CT setting, sulindac alone and DFMO/sulindac combination were effective in reducing tumor number, but not tumor burden growth rate. A decrease in COX-2 staining in DFMO/sulindac CT groups (COX-2, P < 0.01) confirmed the treatment effect. Use of nondestructive OCT enabled repeated, quantitative evaluation of tumor number and burden, allowing changes in these parameters to be measured during CP and as a result of CT. In conclusion, OCT is a robust minimally invasive method for monitoring colorectal cancer disease and effectiveness of therapies in mouse models.
One of the largest factors affecting disease recurrence after surgical cancer resection is negative surgical margins. Hyperspectral imaging (HSI) is an optical imaging technique with potential to serve as a computer aided diagnostic tool for identifying cancer in gross ex-vivo specimens. We developed a tissue classifier using three distinct convolutional neural network (CNN) architectures on HSI data to investigate the ability to classify the cancer margins from ex-vivo human surgical specimens, collected from 20 patients undergoing surgical cancer resection as a preliminary validation group. A new approach for generating the HSI ground truth using a registered histological cancer margin is applied in order to create a validation dataset. The CNN-based method classifies the tumor-normal margin of squamous cell carcinoma (SCCa) versus normal oral tissue with an area under the curve (AUC) of 0.86 for inter-patient validation, performing with 81% accuracy, 84% sensitivity, and 77% specificity. Thyroid carcinoma cancer-normal margins are classified with an AUC of 0.94 for inter-patient validation, performing with 90% accuracy, 91% sensitivity, and 88% specificity. Our preliminary results on a limited patient dataset demonstrate the predictive ability of HSI-based cancer margin detection, which warrants further investigation with more patient data and additional processing techniques to optimize the proposed deep learning method.
The use of regional connectivity measurements derived from diffusion imaging datasets has become of considerable interest in the neuroimaging community in order to better understand cortical and subcortical white matter connectivity. Current connectivity assessment methods are based on streamline fiber tractography, usually applied in a Monte-Carlo fashion. In this work we present a novel, graph-based method that performs a fully deterministic, efficient and stable connectivity computation. The method handles crossing fibers and deals well with multiple seed regions. The computation is based on a multi-directional graph propagation method applied to sampled orientation distribution function (ODF), which can be computed directly from the original diffusion imaging data. We show early results of our method on synthetic and real datasets. The results illustrate the potential of our method towards subjectspecific connectivity measurements that are performed in an efficient, stable and reproducible manner. Such individual connectivity measurements would be well suited for application in population studies of neuropathology, such as Autism, Huntington's Disease, Multiple Sclerosis or leukodystrophies. The proposed method is generic and could easily be applied to non-diffusion data as long as local directional data can be derived.
We present a novel light source specifically tailored for stimulated Raman scattering–spectroscopic optical coherence tomography (SRS-SOCT), which is, to the best of our knowledge, a novel molecular imaging method that combines the molecular sensitivity of SRS with the spatial and spectral multiplexing capabilities of SOCT. The novel laser consists of an 8 W, 450 fs Yb:KGW oscillator, with a repetition rate of 40 MHz, which delivers the Stokes beam for SRS-SOCT and also pumps and amplifies an optical parametric oscillator (OPO). The output of the amplified OPO is then frequency doubled and coherently broadened using a custom-made tapered fiber that generates bandwidth pulses >40 nm, compressible to <50 fs, with the average power over 150 mW, near the shot-noise limit above 250 kHz. The broadened and compressed pulse simultaneously serves as the pump beam and SOCT light source for SRS-SOCT. This light source is assessed for SRS-SOCT, and its implications for other imaging methods are discussed.