Multi-Level Batch Normalization In Deep Networks For Invasive Ductal Carcinoma Cell Discrimination In Histopathology Images

Breast cancer is the most diagnosed cancer and the most predominant cause of death in women worldwide. Imaging techniques such as the breast cancer pathology helps in the diagnosis and monitoring of the disease. However identification of malignant cells can be challenging given the high heterogeneity in tissue absorbotion from staining agents. In this work, we present a novel approach for Invasive Ductal Carcinoma (IDC) cells discrimination in histopathology slides. We propose a model derived from the Inception architecture, proposing a multi-level batch normalization module between each convolutional steps. This module was used as a base block for the feature extraction in a CNN architecture. We used the open IDC dataset in which we obtained a balanced accuracy of 0.89 and an F1 score of 0.90, thus surpassing recent state of the art classification algorithms tested on this public dataset.Comment: 4 pages, 5 figure

Liver lesion segmentation informed by joint liver segmentation

We propose a model for the joint segmentation of the liver and liver lesions in computed tomography (CT) volumes. We build the model from two fully convolutional networks, connected in tandem and trained together end-to-end. We evaluate our approach on the 2017 MICCAI Liver Tumour Segmentation Challenge, attaining competitive liver and liver lesion detection and segmentation scores across a wide range of metrics. Unlike other top performing methods, our model output post-processing is trivial, we do not use data external to the challenge, and we propose a simple single-stage model that is trained end-to-end. However, our method nearly matches the top lesion segmentation performance and achieves the second highest precision for lesion detection while maintaining high recall.Comment: Late upload of conference version (ISBI

Deductive Optimization of Relational Data Storage

Optimizing the physical data storage and retrieval of data are two key database management problems. In this paper, we propose a language that can express a wide range of physical database layouts, going well beyond the row- and column-based methods that are widely used in database management systems. We use deductive synthesis to turn a high-level relational representation of a database query into a highly optimized low-level implementation which operates on a specialized layout of the dataset. We build a compiler for this language and conduct experiments using a popular database benchmark, which shows that the performance of these specialized queries is competitive with a state-of-the-art in memory compiled database system

Do Not Forget the "How" along with the "What": Improving the Transparency of Sustainability Reports

Considerable resources are invested in producing sustainability reports, yet few organizations reap the transparency benefits they promise. This article explores the way ten leading global fashion companies use a combination of data visualization and placement, stakeholder-driven interactive content, and multi-media and immersive content to build the trust necessary to improve their reporting and transparency. While few organizations have the resources of the global fashion giants, this article proposes a four-stage framework that guides managers through a step-change of systematic and targeted improvement

THE PERFORMANCE OF BDS RELATIVE POSITIONING USAGE WITH REAL OBSERVATION DATA

With the first phase of COMPASS/BeiDou-2 (BDS) completed, the assessment ofpositioning performance and the characterization of its system are analyzed andpresented. Pseudo-range and carrier phase measurements modulated on B1 and B2have been collected in Shanghai, from 00:00 to 24:00 on 28 December, 2012.Compared with GPS, visibility and measurement quality of BDS’s GEO, IGSO andMEO satellites are analyzed. DOP during the whole orbital period is also analyzedthe results demonstrate that BDS’s HDOP is better than GPS’s one, but VDOPopposite. Furthermore, the result of positioning is also presented and analyzed.Short baselines are estimated by standalone BDS and GPS’s carrier phasemeasurement, respectively, using 48 segmentations of observations during a wholeday (24 hours, each segmentation, is about 30 minutes observation). The analysis ofstatic relative positioning demonstrates that BDS could achieve to millimeter level,corresponding to GPS. Kinematic result is produced by double differenced carrierphase observations with the ambiguities fixed under the constraint of precise shortbaseline.The result shows that the centimeter accuracy could be achieved. Whencomparing the results of kinematic baseline solutions, performance of BDS is worsethan GPS on North and Up components, but oppositely on the component of East inthe kinematic baseline processing