24,773 research outputs found
New marked point process models for microscopy images
In developing new materials, the characterization of microstructures is one of the key steps. To characterize the microstructure, many microscope modalities have been devised and improved over decades. With the increase in image resolution in the spatial and time domains, the amount of image data keeps increasing in the fields such as materials science and biomedical engineering. As a result, image processing plays a critical role in this era of science and technology. In materials image analysis, image segmentation and feature detection are considered very important.
The first part of this research aims to resolve the segmentation problem caused by blurring artifacts in scanning electron microscopy (SEM) images. This blurring issue can lead to a bridged channel problem, which becomes an obstacle in analyzing the microstructures. To tackle the problem, we propose a joint deconvolution and segmentation (JDS) method. As a segmentation method, we use the expectation-maximization/maximization of the posterior marginals (EM/MPM) method, using the Markov random field (MRF) prior model. Experiments show the proposed method improves the segmentation result at object boundaries.
The next phase of the image segmentation is detecting image features. In the second part of this research, we detect channel configurations in materials images. We propose a new approach of channel identification, based on the marked point process (MPP) framework, to effectively detect channels in materials images. To describe a higher level of structures in an image, the MPP framework is more effective than the MRF prior model. The reversible-jump Markov chain Monte Carlo (RJMCMC) algorithm embedded with simulated annealing is used as an optimization method, and a new switching kernel in an RJMCMC is used to reduce computational time. The channel configuration is useful in characterizing materials images. In addition, this information can be used to reduce the bridged channel problem more effectively.
In materials image processing, one of the most important goals of feature detection is identifying the 3D structure of objects from 3D microscope datasets. The final part of this research is to perform fast and accurate estimation of 3D object configurations from a 3D dataset. We propose a fast 3D fitting method to improve the computational complexity over a full-search 3D MPP method. Experiments show that the fast 3D fitting method significantly decreases execution time compared to the full 3D MPP method
Field-portable pixel super-resolution colour microscope.
Based on partially-coherent digital in-line holography, we report a field-portable microscope that can render lensfree colour images over a wide field-of-view of e.g., >20 mm(2). This computational holographic microscope weighs less than 145 grams with dimensions smaller than 17×6×5 cm, making it especially suitable for field settings and point-of-care use. In this lensfree imaging design, we merged a colorization algorithm with a source shifting based multi-height pixel super-resolution technique to mitigate 'rainbow' like colour artefacts that are typical in holographic imaging. This image processing scheme is based on transforming the colour components of an RGB image into YUV colour space, which separates colour information from brightness component of an image. The resolution of our super-resolution colour microscope was characterized using a USAF test chart to confirm sub-micron spatial resolution, even for reconstructions that employ multi-height phase recovery to handle dense and connected objects. To further demonstrate the performance of this colour microscope Papanicolaou (Pap) smears were also successfully imaged. This field-portable and wide-field computational colour microscope could be useful for tele-medicine applications in resource poor settings
Interfacial charge transfer in nanoscale polymer transistors
Interfacial charge transfer plays an essential role in establishing the
relative alignment of the metal Fermi level and the energy bands of organic
semiconductors. While the details remain elusive in many systems, this charge
transfer has been inferred in a number of photoemission experiments. We present
electronic transport measurements in very short channel ( nm)
transistors made from poly(3-hexylthiophene) (P3HT). As channel length is
reduced, the evolution of the contact resistance and the zero-gate-voltage
conductance are consistent with such charge transfer. Short channel conduction
in devices with Pt contacts is greatly enhanced compared to analogous devices
with Au contacts, consistent with charge transfer expectations. Alternating
current scanning tunneling microscopy (ACSTM) provides further evidence that
holes are transferred from Pt into P3HT, while much less charge transfer takes
place at the Au/P3HT interface.Comment: 19 preprint pages, 6 figure
Imaging ductal carcinoma using a hyperspectral imaging system
Hyperspectral Imaging (HSI) is a non-invasive optical imaging modality that shows the potential to aid pathologists in breast cancer diagnoses cases. In this study, breast cancer tissues from different patients were imaged by a hyperspectral system to detect spectral differences between normal and breast cancer tissues, as well as early and late stages of breast cancer. If the spectral differences in these tissue types can be measured, automated systems can be developed to help the pathologist identify suspect biopsy samples, which will improve sample throughput and assist in making critical treatment decisions. Tissue samples from ten different patients were provided by the WVU Pathology Department. The samples from each patient included both normal and ductal carcinoma tissue, both stained and unstained. These cells were imaged using a snapshot HSI system, and the spectral reflectances were evaluated to see if there was a measurable spectral difference between the various cell types. Analysis of the spectral reflectance values indicated that wavelengths near 550nm show the best differentiation between tissue types. This information was used to train image processing algorithms using supervised and unsupervised data. K-Means and Support Vector Machine (SVM) approaches were applied to the hyperspectral data cubes, and successfully detected spectral tissue differences with sensitivity of 85.45%, and specificity of 94.64% with TNR of 95.8%, and FPR of 4.2%. These results were verified by ground truth marking of the tissue samples by a pathologist. This interdisciplinary work will build a bridge between pathology and hyperspectral optical diagnostic imaging in order to reduce time and workload on the pathologist, which can lead to benefit of lead reducing time, and increasing the accuracy of diagnoses
The Boston University Photonics Center annual report 2013-2014
This repository item contains an annual report that summarizes activities of the Boston University Photonics Center in the 2013-2014 academic year. The report provides quantitative and descriptive information regarding photonics programs in education, interdisciplinary research, business innovation, and technology development. The Boston University Photonics Center (BUPC) is an interdisciplinary hub for education, research, scholarship, innovation, and technology development associated with practical uses of light.This annual report summarizes activities of the Boston University Photonics Center in the 2013–2014 academic year.This has been a good year for the Photonics Center. In the following pages, you will see that the center’s faculty received prodigious honors and awards, generated more than 100 notable scholarly publications in the leading journals in our field, and attracted 20M in research funding for the University, are indicative of the breadth of Photonics Center research interests: from fundamental modeling of optoelectronic materials to practical development of cancer diagnostics, from exciting new discoveries in optogenetics for understanding brain function to the achievement of world-record resolution in semiconductor circuit microscopy. Our community welcomed an auspicious cohort of new faculty members, including a newly hired assistant professor and a newly hired professor (and Chair of the Mechanical Engineering Department). The Industry/University Cooperative Research Center—the centerpiece of our translational biophotonics program—continues to focus on advancing the health care and medical device industries, and has entered its fourth year of operation with a strong record of achievement and with the support of an enthusiastic industrial membership base
The Boston University Photonics Center annual report 2013-2014
This repository item contains an annual report that summarizes activities of the Boston University Photonics Center in the 2013-2014 academic year. The report provides quantitative and descriptive information regarding photonics programs in education, interdisciplinary research, business innovation, and technology development. The Boston University Photonics Center (BUPC) is an interdisciplinary hub for education, research, scholarship, innovation, and technology development associated with practical uses of light.This annual report summarizes activities of the Boston University Photonics Center in the 2013–2014 academic year.This has been a good year for the Photonics Center. In the following pages, you will see that the center’s faculty received prodigious honors and awards, generated more than 100 notable scholarly publications in the leading journals in our field, and attracted 20M in research funding for the University, are indicative of the breadth of Photonics Center research interests: from fundamental modeling of optoelectronic materials to practical development of cancer diagnostics, from exciting new discoveries in optogenetics for understanding brain function to the achievement of world-record resolution in semiconductor circuit microscopy. Our community welcomed an auspicious cohort of new faculty members, including a newly hired assistant professor and a newly hired professor (and Chair of the Mechanical Engineering Department). The Industry/University Cooperative Research Center—the centerpiece of our translational biophotonics program—continues to focus on advancing the health care and medical device industries, and has entered its fourth year of operation with a strong record of achievement and with the support of an enthusiastic industrial membership base
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