Towards Optimal Image Stitching for Virtual Microscopy

In this paper we present an image stitching method based on dynamic programming and describe its application to automated slide acquisition for Virtual Microscopy (VM). Given a large number of fields of view (FOVs) acquired from a single microscope slide, we composite these images into a single large 'virtual slide' image. The location of each FOV is determined using a new algorithm based on dynamic programming. We compare the performance of the proposed algorithm to an existing greedy algorithm. In a visual trial it is shown that the new algorithm provides a significant improvement in perceived image quality at image boundaries compared to the existing algorithm

Virtual Microscopy with Extended Depth of Field

In this paper, we describe a virtual microscope system, based on JPEG 2000, which utilizes extended depth of field (EDF) imaging. Through a series of observer trials we show that EDF imaging improves both the local image quality of individual fields of view (FOV) and the accuracy with which the FOVs can be mosaiced (stitched) together. In addition, we estimate the required bit rate to adequately render a set of histology and cytology specimens at a quality suitable for on-line learning and collaboration. We show that, using JPEG 2000, we can efficiently represent high-quality, high-resolution colour images of microscopic specimens with less than 1 bit per pixel

Hybrid Method for Digits Recognition using Fixed-Frame Scores and Derived Pitch

This paper presents a procedure of frame normalization based on the traditional dynamic time warping (DTW) using the LPC coefficients. The redefined method is called as the DTW frame-fixing method (DTW-FF), it works by normalizing the word frames of the input against the reference frames. The enthusiasm to this study is due to neural network limitation that entails a fix number of input nodes for when processing multiple inputs in parallel. Due to this problem, this research is initiated to reduce the amount of computation and complexity in a neural network by reducing the number of inputs into the network. In this study, dynamic warping process is used, in which local distance scores of the warping path are fixed and collected so that their scores are of equal number of frames. Also studied in this paper is the consideration of pitch as a contributing feature to the speech recognition. Results showed a good performance and improvement when using pitch along with DTW-FF feature. The convergence rate between using the steepest gradient descent is also compared to another method namely conjugate gradient method. Convergence rate is also improved when conjugate gradient method is introduced in the back-propagation algorithm

A remark on the mean-field dynamics of many-body bosonic systems with random interactions

The mean-field limit for the dynamics of bosons with random interactions is rigorously studied. It is shown that, for interactions that are almost-surely bounded, the many-body quantum evolution can be replaced in the mean-field limit by a single particle nonlinear evolution that is described by the Hartree equation. This is an Egorov-type theorem for many-body quantum systems with random interactions.Comment: 6 page

Teaching histology to first-year veterinary science students using virtual microscopy and traditional microscopy: A comparison of student responses

Virtual microscopy (VM) is a comparatively recent innovation that is revolutionizing both the teaching of microscopic structure in human medicine and the concept of online diagnosis and telemedicine. The interactivity of the various commercially available browsers attempts to simulate the experience of looking down a microscope while offering advantages over traditional microscopy that include clarity of image, reduced infrastructure, and high flexibility, as the images are accessible online. We developed our own VM system, including customized software and a browser that was simple and intuitive to use, with the added advantage of further modifications possible to assist student learning. In this article, we report on a preliminary study wherein VM was introduced to veterinary science students in one course and directly compared to traditional microscopy to determine whether students would readily accept this new technology and which aspects of VM were advantageous. Responses from a survey form showed that students rated VM significantly higher than traditional microscopy as a tool to learn histology because it offers clearer images, the ability to learn collaboratively, more effective use of time, and the flexibility of online learning. Students also indicated a strong preference for the use of VM in future courses. These results suggest that VM is a flexible and enjoyable resource that could be useful to enhance the learning of microscopic structure in veterinary science courses

Comparison between PUN and Tofts models in the quantification of dynamic contrast-enhanced MR imaging

Dynamic contrast-enhanced study in magnetic resonance imaging (DCE-MRI) is an important tool in oncology to visualize tissues vascularization and to define tumour aggressiveness on the basis of an altered perfusion and permeability. Pharmacokinetic models are generally used to extract hemodynamic parameters, providing a quantitative description of the contrast uptake and wash-out. Empirical functions can also be used to fit experimental data without the need of any assumption about tumour physiology, as in pharmacokinetic models, increasing their diagnostic utility, in particular when automatic diagnosis systems are implemented on the basis of an MRI multi-parametric approach. Phenomenological universalities (PUN) represent a novel tool for experimental research and offer a simple and systematic method to represent a set of data independent of the application field. DCE-MRI acquisitions can thus be advantageously evaluated by the extended PUN class, providing a convenient diagnostic tool to analyse functional studies, adding a new set of features for the classification of malignant and benign lesions in computer aided detection systems. In this work the Tofts pharmacokinetic model and the class EU1 generated by the PUN description were compared in the study of DCE-MRI of the prostate, evaluating complexity of model implementation, goodness of fitting results, classification performances and computational cost. The mean R2 obtained with the EU1 and Tofts model were equal to 0.96 and 0.90, respectively, and the classification performances achieved by the EU1 model and the Tofts implementation discriminated malignant from benign tissues with an area under the receiver operating characteristic curve equal to 0.92 and 0.91, respectively. Furthermore, the EU1 model has a simpler functional form which reduces implementation complexity and computational time, requiring 6 min to complete a patient elaboration process, instead of 8 min needed for the Tofts model analysi